uid int64 2 364k | orig_metric stringclasses 30
values | sklearn_metric stringclasses 9
values | dataset_name stringlengths 2 124 | dataset_description stringlengths 3 13k ⌀ | dataset_features stringlengths 41 3.57M | task_description stringlengths 627 762 | task_name stringlengths 2 124 | attribute_names listlengths 0 100k | categorical_indicator listlengths 0 100k | __index_level_0__ int64 0 3.8k |
|---|---|---|---|---|---|---|---|---|---|---|
363,775 | mean_absolute_error | mean_absolute_error | LimeSoda_SA.112_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOC_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
3: [3 - Altitude (numeric)],
4: [4 - Slope (numeric)],
5: [5 - ERa (numeric)],
6: [6 - G_Total_Counts (numeric)],
7: [7 - G_K (numeric)],
8: [8 - G_U (numeric)],
9: [9 - G_Th (numeric)],
10: [10 - G_Cs (numeric)],
1... | {'MajorityClassSize': nan,
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'NumberOfClasses': 0.0,
'NumberOfFeatures': 1415.0,
'NumberOfInstances': 112.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 1415.0,
'NumberOfSymbolicFeatures': 0.0,
... | LimeSoda_SA.112_dataset | [
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"Clay_target",
"Altitude",
"Slope",
"ERa",
"G_Total_Counts",
"G_K",
"G_U",
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"G_Cs",
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f... | 1,240 |
243 | predictive_accuracy | accuracy_score | breast-cancer | **Author**:
**Source**: Unknown -
**Please cite**:
Citation Request:
This breast cancer domain was obtained from the University Medical Centre,
Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and
M. Soklic for providing the data. Please include this citation if you plan
... | {0: [0 - age (nominal)],
1: [1 - menopause (nominal)],
2: [2 - tumor-size (nominal)],
3: [3 - inv-nodes (nominal)],
4: [4 - node-caps (nominal)],
5: [5 - deg-malig (nominal)],
6: [6 - breast (nominal)],
7: [7 - breast-quad (nominal)],
8: [8 - irradiat (nominal)],
9: [9 - Class (nominal)]} | {'MajorityClassSize': 201.0,
'MaxNominalAttDistinctValues': 11.0,
'MinorityClassSize': 85.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 286.0,
'NumberOfInstancesWithMissingValues': 9.0,
'NumberOfMissingValues': 9.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 10.0,
... | breast-cancer | [
"age",
"menopause",
"tumor-size",
"inv-nodes",
"node-caps",
"deg-malig",
"breast",
"breast-quad",
"irradiat"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
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] | 1,241 |
248 | predictive_accuracy | accuracy_score | mfeat-morphological | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Morphological**
One of a set ... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - class (nominal)]} | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 7.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 1.0,
... | mfeat-morphological | [
"att1",
"att2",
"att3",
"att4",
"att5",
"att6"
] | [
false,
false,
false,
false,
false,
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] | 1,242 |
363,780 | mean_absolute_error | mean_absolute_error | LimeSoda_SSP.460_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOC_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
3: [3 - wl_350 (numeric)],
4: [4 - wl_352 (numeric)],
5: [5 - wl_353 (numeric)],
6: [6 - wl_355 (numeric)],
7: [7 - wl_357 (numeric)],
8: [8 - wl_359 (numeric)],
9: [9 - wl_360 (numeric)],
10: [10 - wl_362 (numeric)]... | {'MajorityClassSize': nan,
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'NumberOfClasses': 0.0,
'NumberOfFeatures': 833.0,
'NumberOfInstances': 460.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 833.0,
'NumberOfSymbolicFeatures': 0.0,
'c... | LimeSoda_SSP.460_dataset | [
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"Clay_target",
"wl_350",
"wl_352",
"wl_353",
"wl_355",
"wl_357",
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"wl_362",
"wl_364",
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"wl_375",
"wl_376",
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f... | 1,243 |
363,372 | root_mean_squared_error | root_mean_squared_error | bookprice_prediction | Predict the sale price of books based on text features like their title, author, synopsis, categorical features like genre and numeric features like customer reviews and overall
rating. This dataset originally stems from a 2019 MachineHack prediction competition:
https://machinehack.com/hackathons/predict_the_p... | {0: [0 - Title (string)],
1: [1 - Author (string)],
2: [2 - Edition (string)],
3: [3 - Reviews (numeric)],
4: [4 - Ratings (numeric)],
5: [5 - Synopsis (string)],
6: [6 - Genre (string)],
7: [7 - BookCategory (string)],
8: [8 - Price (numeric)]} | {'MajorityClassSize': nan,
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'NumberOfFeatures': 9.0,
'NumberOfInstances': 4989.0,
'NumberOfInstancesWithMissingValues': 831.0,
'NumberOfMissingValues': 831.0,
'NumberOfNumericFeatures': 3.0,
'NumberOfSymbolicFeatures': 0.0,
'... | bookprice_prediction | [
"Title",
"Author",
"Edition",
"Reviews",
"Ratings",
"Synopsis",
"Genre",
"BookCategory"
] | [
false,
false,
false,
false,
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] | 1,244 |
253 | predictive_accuracy | accuracy_score | cmc | **Author**: [Tjen-Sien Lim](limt@stat.wisc.edu)
**Source**: [As obtained from UCI](https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice)
**Please cite**: [UCI citation](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Contraceptive Method Choice
2. Sources:
(a) Origin: This datase... | {0: [0 - Wifes_age (numeric)],
1: [1 - Wifes_education (nominal)],
2: [2 - Husbands_education (nominal)],
3: [3 - Number_of_children_ever_born (numeric)],
4: [4 - Wifes_religion (nominal)],
5: [5 - Wifes_now_working%3F (nominal)],
6: [6 - Husbands_occupation (nominal)],
7: [7 - Standard-of-living_index (nominal)... | {'MajorityClassSize': 629.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 333.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 1473.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2.0,
'NumberOfSymbolicFeatures': 8.0,
... | cmc | [
"Wifes_age",
"Wifes_education",
"Husbands_education",
"Number_of_children_ever_born",
"Wifes_religion",
"Wifes_now_working%3F",
"Husbands_occupation",
"Standard-of-living_index",
"Media_exposure"
] | [
false,
true,
true,
false,
true,
true,
true,
true,
true
] | 1,245 |
241 | predictive_accuracy | accuracy_score | balance-scale | **Author**: Siegler, R. S. (donated by Tim Hume)
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/balance+scale) - 1994
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Balance Scale Weight & Distance Database**
This data set was generated to model psychological experiment... | {0: [0 - left-weight (numeric)],
1: [1 - left-distance (numeric)],
2: [2 - right-weight (numeric)],
3: [3 - right-distance (numeric)],
4: [4 - class (nominal)]} | {'MajorityClassSize': 288.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 49.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 5.0,
'NumberOfInstances': 625.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 4.0,
'NumberOfSymbolicFeatures': 1.0,
'co... | balance-scale | [
"left-weight",
"left-distance",
"right-weight",
"right-distance"
] | [
false,
false,
false,
false
] | 1,246 |
235 | predictive_accuracy | accuracy_score | arrhythmia | **Author**: H. Altay Guvenir, Burak Acar, Haldun Muderrisoglu
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/arrhythmia)
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Cardiac Arrhythmia Database**
The aim is to determine the type of arrhythmia from the ECG recordings. ... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - height (numeric)],
3: [3 - weight (numeric)],
4: [4 - QRSduration (numeric)],
5: [5 - PRinterval (numeric)],
6: [6 - Q-Tinterval (numeric)],
7: [7 - Tinterval (numeric)],
8: [8 - Pinterval (numeric)],
9: [9 - QRS (numeric)],
10: [10 - T (numeric)],
11:... | {'MajorityClassSize': 245.0,
'MaxNominalAttDistinctValues': 13.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 13.0,
'NumberOfFeatures': 280.0,
'NumberOfInstances': 452.0,
'NumberOfInstancesWithMissingValues': 384.0,
'NumberOfMissingValues': 408.0,
'NumberOfNumericFeatures': 206.0,
'NumberOfSymbolicFeatures': ... | arrhythmia | [
"age",
"sex",
"height",
"weight",
"QRSduration",
"PRinterval",
"Q-Tinterval",
"Tinterval",
"Pinterval",
"QRS",
"T",
"P",
"QRST",
"J",
"heartrate",
"chDI_Qwave",
"chDI_Rwave",
"chDI_Swave",
"chDI_RPwave",
"chDI_SPwave",
"chDI_intrinsicReflecttions",
"chDI_RRwaveExists",
"c... | [
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tr... | 1,247 |
363,760 | mean_absolute_error | mean_absolute_error | LimeSoda_CV.98_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOC_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
3: [3 - wl_350 (numeric)],
4: [4 - wl_351 (numeric)],
5: [5 - wl_352 (numeric)],
6: [6 - wl_353 (numeric)],
7: [7 - wl_354 (numeric)],
8: [8 - wl_355 (numeric)],
9: [9 - wl_356 (numeric)],
10: [10 - wl_357 (numeric)]... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
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'NumberOfClasses': 0.0,
'NumberOfFeatures': 2154.0,
'NumberOfInstances': 98.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2154.0,
'NumberOfSymbolicFeatures': 0.0,
'... | LimeSoda_CV.98_dataset | [
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"Clay_target",
"wl_350",
"wl_351",
"wl_352",
"wl_353",
"wl_354",
"wl_355",
"wl_356",
"wl_357",
"wl_358",
"wl_359",
"wl_360",
"wl_361",
"wl_362",
"wl_363",
"wl_364",
"wl_365",
"wl_366",
"wl_367",
"wl_368",
"wl_369",
"wl_370",
"wl_371",
"wl_372",
"wl_373"... | [
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f... | 1,248 |
245 | predictive_accuracy | accuracy_score | breast-w | **Author**: Dr. William H. Wolberg, University of Wisconsin
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(original)), [University of Wisconsin](http://pages.cs.wisc.edu/~olvi/uwmp/cancer.html) - 1995
**Please cite**: See below, plus [UCI](https://archive.ics.uci.edu/ml/citation_... | {0: [0 - Clump_Thickness (numeric)],
1: [1 - Cell_Size_Uniformity (numeric)],
2: [2 - Cell_Shape_Uniformity (numeric)],
3: [3 - Marginal_Adhesion (numeric)],
4: [4 - Single_Epi_Cell_Size (numeric)],
5: [5 - Bare_Nuclei (numeric)],
6: [6 - Bland_Chromatin (numeric)],
7: [7 - Normal_Nucleoli (numeric)],
8: [8 - M... | {'MajorityClassSize': 458.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 241.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 699.0,
'NumberOfInstancesWithMissingValues': 16.0,
'NumberOfMissingValues': 16.0,
'NumberOfNumericFeatures': 9.0,
'NumberOfSymbolicFeatures': 1.0,
... | breast-w | [
"Clump_Thickness",
"Cell_Size_Uniformity",
"Cell_Shape_Uniformity",
"Marginal_Adhesion",
"Single_Epi_Cell_Size",
"Bare_Nuclei",
"Bland_Chromatin",
"Normal_Nucleoli",
"Mitoses"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,250 |
211,826 | predictive_accuracy | accuracy_score | parkinson-speech-uci | Source:
C. Okan Sakar a, Gorkem Serbes b, Aysegul Gunduz c,
Hunkar C. Tunc a, Hatice Nizam d, Betul Erdogdu Sakar e, Melih Tutuncu c,
Tarkan Aydin a, M. Erdem Isenkul d, Hulya Apaydin c
a Department of Computer Engineering, Bahcesehir University, Istanbul, 34353, Turkey
b Department of Biomedical Engineering, Yildiz T... | {0: [0 - id (numeric)],
1: [1 - gender (numeric)],
2: [2 - PPE (numeric)],
3: [3 - DFA (numeric)],
4: [4 - RPDE (numeric)],
5: [5 - numPulses (numeric)],
6: [6 - numPeriodsPulses (numeric)],
7: [7 - meanPeriodPulses (numeric)],
8: [8 - stdDevPeriodPulses (numeric)],
9: [9 - locPctJitter (numeric)],
10: [10 - ... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
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'NumberOfClasses': 0.0,
'NumberOfFeatures': 754.0,
'NumberOfInstances': 756.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 754.0,
'NumberOfSymbolicFeatures': 0.0,
'c... | parkinson-speech-uci | [
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f... | 1,252 |
233 | predictive_accuracy | accuracy_score | kr-vs-kp | Author: Alen Shapiro
Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Chess+(King-Rook+vs.+King-Pawn))
Please cite: [UCI citation policy](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Chess End-Game -- King+Rook versus King+Pawn on a7
(usually abbreviated KRKPA7). The pawn on a7 means it is one s... | {0: [0 - bkblk (nominal)],
1: [1 - bknwy (nominal)],
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4: [4 - bkspr (nominal)],
5: [5 - bkxbq (nominal)],
6: [6 - bkxcr (nominal)],
7: [7 - bkxwp (nominal)],
8: [8 - blxwp (nominal)],
9: [9 - bxqsq (nominal)],
10: [10 - cntxt (nominal)],
11: [11 - dsopp (nom... | {'MajorityClassSize': 1669.0,
'MaxNominalAttDistinctValues': 3.0,
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'NumberOfInstancesWithMissingValues': 0.0,
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'NumberOfSymbolicFeatures': 37.0... | kr-vs-kp | [
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265 | predictive_accuracy | accuracy_score | dermatology | 1. Title: Dermatology Database
2. Source Information:
(a) Original owners:
-- 1. Nilsel Ilter, M.D., Ph.D.,
Gazi University,
School of Medicine
06510 Ankara, Turkey
Phone: +90 (312) 214 1080
-- 2. H. Altay Guvenir, PhD.,
Bilkent Univ... | {0: [0 - erythema (nominal)],
1: [1 - scaling (nominal)],
2: [2 - definite_borders (nominal)],
3: [3 - itching (nominal)],
4: [4 - koebner_phenomenon (nominal)],
5: [5 - polygonal_papules (nominal)],
6: [6 - follicular_papules (nominal)],
7: [7 - oral_mucosal_involvement (nominal)],
8: [8 - knee_and_elbow_invol... | {'MajorityClassSize': 112.0,
'MaxNominalAttDistinctValues': 6.0,
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'NumberOfFeatures': 35.0,
'NumberOfInstances': 366.0,
'NumberOfInstancesWithMissingValues': 8.0,
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'NumberOfSymbolicFeatures': 34.0,
'... | dermatology | [
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"itching",
"koebner_phenomenon",
"polygonal_papules",
"follicular_papules",
"oral_mucosal_involvement",
"knee_and_elbow_involvement",
"scalp_involvement",
"family_history",
"melanin_incontinence",
"eosinophils_in_the_infiltrate",
"PNL_infiltrate",... | [
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] | 1,254 |
363,792 | mean_absolute_error | mean_absolute_error | bkd1kmc1Dataset5 | Dataset bkd1kmcDataset5 pour test OpenML | {0: [0 - pixel_0_0 (numeric)],
1: [1 - pixel_0_1 (numeric)],
2: [2 - pixel_0_2 (numeric)],
3: [3 - pixel_0_3 (numeric)],
4: [4 - pixel_0_4 (numeric)],
5: [5 - pixel_0_5 (numeric)],
6: [6 - pixel_0_6 (numeric)],
7: [7 - pixel_0_7 (numeric)],
8: [8 - pixel_1_0 (numeric)],
9: [9 - pixel_1_1 (numeric)],
10: [10 -... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 65.0,
'NumberOfInstances': 1797.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 65.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | bkd1kmc1Dataset5 | [
"pixel_0_0",
"pixel_0_1",
"pixel_0_2",
"pixel_0_3",
"pixel_0_4",
"pixel_0_5",
"pixel_0_6",
"pixel_0_7",
"pixel_1_0",
"pixel_1_1",
"pixel_1_2",
"pixel_1_3",
"pixel_1_4",
"pixel_1_5",
"pixel_1_6",
"pixel_1_7",
"pixel_2_0",
"pixel_2_1",
"pixel_2_2",
"pixel_2_3",
"pixel_2_4",
"... | [
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f... | 1,255 |
268 | predictive_accuracy | accuracy_score | ecoli | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Protein Localization Sites
2. Creator and Maintainer:
Kenta Nakai
Institue of Molecular and Cellular Biology
Osaka, University
1-3 Yamada-oka, Suita 565 Japan
nakai@imcb.osaka-u.ac.jp
http... | {0: [0 - mcg (numeric)],
1: [1 - gvh (numeric)],
2: [2 - lip (numeric)],
3: [3 - chg (numeric)],
4: [4 - aac (numeric)],
5: [5 - alm1 (numeric)],
6: [6 - alm2 (numeric)],
7: [7 - class (nominal)]} | {'MajorityClassSize': 143.0,
'MaxNominalAttDistinctValues': 8.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 8.0,
'NumberOfFeatures': 8.0,
'NumberOfInstances': 336.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 7.0,
'NumberOfSymbolicFeatures': 1.0,
'cos... | ecoli | [
"mcg",
"gvh",
"lip",
"chg",
"aac",
"alm1",
"alm2"
] | [
false,
false,
false,
false,
false,
false,
false
] | 1,256 |
269 | predictive_accuracy | accuracy_score | sonar | **Author**:
**Source**: Unknown -
**Please cite**:
NAME: Sonar, Mines vs. Rocks
SUMMARY: This is the data set used by Gorman and Sejnowski in their study
of the classification of sonar signals using a neural network [1]. The
task is to train a network to discriminate between sonar signals bounced
off a... | {0: [0 - attribute_1 (numeric)],
1: [1 - attribute_2 (numeric)],
2: [2 - attribute_3 (numeric)],
3: [3 - attribute_4 (numeric)],
4: [4 - attribute_5 (numeric)],
5: [5 - attribute_6 (numeric)],
6: [6 - attribute_7 (numeric)],
7: [7 - attribute_8 (numeric)],
8: [8 - attribute_9 (numeric)],
9: [9 - attribute_10 (... | {'MajorityClassSize': 111.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 97.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 61.0,
'NumberOfInstances': 208.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 60.0,
'NumberOfSymbolicFeatures': 1.0,
'... | sonar | [
"attribute_1",
"attribute_2",
"attribute_3",
"attribute_4",
"attribute_5",
"attribute_6",
"attribute_7",
"attribute_8",
"attribute_9",
"attribute_10",
"attribute_11",
"attribute_12",
"attribute_13",
"attribute_14",
"attribute_15",
"attribute_16",
"attribute_17",
"attribute_18",
"... | [
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f... | 1,257 |
259 | predictive_accuracy | accuracy_score | credit-approval | **Author**: Confidential - Donated by Ross Quinlan
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/credit+approval) - 1987
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Credit Approval**
This file concerns credit card applications. All attribute names and values have been... | {0: [0 - A1 (nominal)],
1: [1 - A2 (numeric)],
2: [2 - A3 (numeric)],
3: [3 - A4 (nominal)],
4: [4 - A5 (nominal)],
5: [5 - A6 (nominal)],
6: [6 - A7 (nominal)],
7: [7 - A8 (numeric)],
8: [8 - A9 (nominal)],
9: [9 - A10 (nominal)],
10: [10 - A11 (numeric)],
11: [11 - A12 (nominal)],
12: [12 - A13 (nominal)]... | {'MajorityClassSize': 383.0,
'MaxNominalAttDistinctValues': 14.0,
'MinorityClassSize': 307.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 16.0,
'NumberOfInstances': 690.0,
'NumberOfInstancesWithMissingValues': 37.0,
'NumberOfMissingValues': 67.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 10.0... | credit-approval | [
"A1",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
"A8",
"A9",
"A10",
"A11",
"A12",
"A13",
"A14",
"A15"
] | [
true,
false,
false,
true,
true,
true,
true,
false,
true,
true,
false,
true,
true,
false,
false
] | 1,258 |
261 | predictive_accuracy | accuracy_score | credit-g | **Author**: Dr. Hans Hofmann
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)) - 1994
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**German Credit dataset**
This dataset classifies people described by a set of attributes as good or bad credit... | {0: [0 - checking_status (nominal)],
1: [1 - duration (numeric)],
2: [2 - credit_history (nominal)],
3: [3 - purpose (nominal)],
4: [4 - credit_amount (numeric)],
5: [5 - savings_status (nominal)],
6: [6 - employment (nominal)],
7: [7 - installment_commitment (numeric)],
8: [8 - personal_status (nominal)],
9: ... | {'MajorityClassSize': 700.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 300.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 21.0,
'NumberOfInstances': 1000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 7.0,
'NumberOfSymbolicFeatures': 14.0,... | credit-g | [
"checking_status",
"duration",
"credit_history",
"purpose",
"credit_amount",
"savings_status",
"employment",
"installment_commitment",
"personal_status",
"other_parties",
"residence_since",
"property_magnitude",
"age",
"other_payment_plans",
"housing",
"existing_credits",
"job",
"n... | [
true,
false,
true,
true,
false,
true,
true,
false,
true,
true,
false,
true,
false,
true,
true,
false,
true,
false,
true,
true
] | 1,259 |
363,782 | mean_absolute_error | mean_absolute_error | LimeSoda_UL.120_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOM_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
3: [3 - ERa (numeric)],
4: [4 - wl_420 (numeric)],
5: [5 - wl_421 (numeric)],
6: [6 - wl_422 (numeric)],
7: [7 - wl_423 (numeric)],
8: [8 - wl_424 (numeric)],
9: [9 - wl_425 (numeric)],
10: [10 - wl_426 (numeric)],
... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 2085.0,
'NumberOfInstances': 120.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2085.0,
'NumberOfSymbolicFeatures': 0.0,
... | LimeSoda_UL.120_dataset | [
"pH_target",
"Clay_target",
"ERa",
"wl_420",
"wl_421",
"wl_422",
"wl_423",
"wl_424",
"wl_425",
"wl_426",
"wl_427",
"wl_428",
"wl_429",
"wl_430",
"wl_431",
"wl_432",
"wl_433",
"wl_434",
"wl_435",
"wl_436",
"wl_437",
"wl_438",
"wl_439",
"wl_440",
"wl_441",
"wl_442",
... | [
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f... | 1,260 |
264 | predictive_accuracy | accuracy_score | postoperative-patient-data | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Postoperative Patient Data
2. Source Information:
-- Creators: Sharon Summers, School of Nursing, University of Kansas
Medical Center, Kansas City, KS 66160
Linda Woolery, School of Nursing, University of Mis... | {0: [0 - L-CORE (nominal)],
1: [1 - L-SURF (nominal)],
2: [2 - L-O2 (nominal)],
3: [3 - L-BP (nominal)],
4: [4 - SURF-STBL (nominal)],
5: [5 - CORE-STBL (nominal)],
6: [6 - BP-STBL (nominal)],
7: [7 - COMFORT (nominal)],
8: [8 - decision (nominal)]} | {'MajorityClassSize': 64.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 9.0,
'NumberOfInstances': 90.0,
'NumberOfInstancesWithMissingValues': 3.0,
'NumberOfMissingValues': 3.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 9.0,
'cost_... | postoperative-patient-data | [
"L-CORE",
"L-SURF",
"L-O2",
"L-BP",
"SURF-STBL",
"CORE-STBL",
"BP-STBL",
"COMFORT"
] | [
true,
true,
true,
true,
true,
true,
true,
true
] | 1,261 |
232 | predictive_accuracy | accuracy_score | anneal | **Author**: Unknown. Donated by David Sterling and Wray Buntine
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Annealing) - 1990
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
The original Annealing dataset from UCI. The exact meaning of the features and classes is lar... | {0: [0 - family (nominal)],
1: [1 - product-type (nominal)],
2: [2 - steel (nominal)],
3: [3 - carbon (numeric)],
4: [4 - hardness (numeric)],
5: [5 - temper_rolling (nominal)],
6: [6 - condition (nominal)],
7: [7 - formability (nominal)],
8: [8 - strength (numeric)],
9: [9 - non-ageing (nominal)],
10: [10 - ... | {'MajorityClassSize': 684.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 8.0,
'NumberOfClasses': 5.0,
'NumberOfFeatures': 39.0,
'NumberOfInstances': 898.0,
'NumberOfInstancesWithMissingValues': 898.0,
'NumberOfMissingValues': 22175.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 33.... | anneal | [
"family",
"product-type",
"steel",
"carbon",
"hardness",
"temper_rolling",
"condition",
"formability",
"strength",
"non-ageing",
"surface-finish",
"surface-quality",
"enamelability",
"bc",
"bf",
"bt",
"bw%2Fme",
"bl",
"m",
"chrom",
"phos",
"cbond",
"marvi",
"exptl",
"... | [
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true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
false,
false,
true,
true,
true
] | 1,262 |
190,414 | predictive_accuracy | accuracy_score | parkinson-speech-uci | Source:
C. Okan Sakar a, Gorkem Serbes b, Aysegul Gunduz c,
Hunkar C. Tunc a, Hatice Nizam d, Betul Erdogdu Sakar e, Melih Tutuncu c,
Tarkan Aydin a, M. Erdem Isenkul d, Hulya Apaydin c
a Department of Computer Engineering, Bahcesehir University, Istanbul, 34353, Turkey
b Department of Biomedical Engineering, Yildiz T... | {0: [0 - id (numeric)],
1: [1 - gender (numeric)],
2: [2 - PPE (numeric)],
3: [3 - DFA (numeric)],
4: [4 - RPDE (numeric)],
5: [5 - numPulses (numeric)],
6: [6 - numPeriodsPulses (numeric)],
7: [7 - meanPeriodPulses (numeric)],
8: [8 - stdDevPeriodPulses (numeric)],
9: [9 - locPctJitter (numeric)],
10: [10 - ... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 754.0,
'NumberOfInstances': 756.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 754.0,
'NumberOfSymbolicFeatures': 0.0,
'c... | parkinson-speech-uci | [
"gender",
"PPE",
"DFA",
"RPDE",
"numPulses",
"numPeriodsPulses",
"meanPeriodPulses",
"stdDevPeriodPulses",
"locPctJitter",
"locAbsJitter",
"rapJitter",
"ppq5Jitter",
"ddpJitter",
"locShimmer",
"locDbShimmer",
"apq3Shimmer",
"apq5Shimmer",
"apq11Shimmer",
"ddaShimmer",
"meanAuto... | [
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false,
false,
false,
false,
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false,
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f... | 1,263 |
363,791 | mean_absolute_error | mean_absolute_error | bkd1kmc1 | Dataset bkd1kmc1 pour test OpenML | {0: [0 - pixel_0_0 (numeric)],
1: [1 - pixel_0_1 (numeric)],
2: [2 - pixel_0_2 (numeric)],
3: [3 - pixel_0_3 (numeric)],
4: [4 - pixel_0_4 (numeric)],
5: [5 - pixel_0_5 (numeric)],
6: [6 - pixel_0_6 (numeric)],
7: [7 - pixel_0_7 (numeric)],
8: [8 - pixel_1_0 (numeric)],
9: [9 - pixel_1_1 (numeric)],
10: [10 -... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 65.0,
'NumberOfInstances': 1797.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 65.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | bkd1kmc1 | [
"pixel_0_0",
"pixel_0_1",
"pixel_0_2",
"pixel_0_3",
"pixel_0_4",
"pixel_0_5",
"pixel_0_6",
"pixel_0_7",
"pixel_1_0",
"pixel_1_1",
"pixel_1_2",
"pixel_1_3",
"pixel_1_4",
"pixel_1_5",
"pixel_1_6",
"pixel_1_7",
"pixel_2_0",
"pixel_2_1",
"pixel_2_2",
"pixel_2_3",
"pixel_2_4",
"... | [
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f... | 1,264 |
363,778 | mean_absolute_error | mean_absolute_error | LimeSoda_SL.125_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOM_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
3: [3 - ERa (numeric)],
4: [4 - wl_420 (numeric)],
5: [5 - wl_421 (numeric)],
6: [6 - wl_422 (numeric)],
7: [7 - wl_423 (numeric)],
8: [8 - wl_424 (numeric)],
9: [9 - wl_425 (numeric)],
10: [10 - wl_426 (numeric)],
... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 2085.0,
'NumberOfInstances': 125.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2085.0,
'NumberOfSymbolicFeatures': 0.0,
... | LimeSoda_SL.125_dataset | [
"pH_target",
"Clay_target",
"ERa",
"wl_420",
"wl_421",
"wl_422",
"wl_423",
"wl_424",
"wl_425",
"wl_426",
"wl_427",
"wl_428",
"wl_429",
"wl_430",
"wl_431",
"wl_432",
"wl_433",
"wl_434",
"wl_435",
"wl_436",
"wl_437",
"wl_438",
"wl_439",
"wl_440",
"wl_441",
"wl_442",
... | [
false,
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false,
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false,
false,
false,
false,
false,
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false,
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f... | 1,265 |
270 | predictive_accuracy | accuracy_score | glass | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Glass Identification Database
2. Sources:
(a) Creator: B. German
-- Central Research Establishment
Home Office Forensic Science Service
Aldermaston, Reading, Berkshire RG7 4PN
(b) Donor: Vina Spiehler, P... | {0: [0 - RI (numeric)],
1: [1 - Na (numeric)],
2: [2 - Mg (numeric)],
3: [3 - Al (numeric)],
4: [4 - Si (numeric)],
5: [5 - K (numeric)],
6: [6 - Ca (numeric)],
7: [7 - Ba (numeric)],
8: [8 - Fe (numeric)],
9: [9 - Type (nominal)]} | {'MajorityClassSize': 76.0,
'MaxNominalAttDistinctValues': 6.0,
'MinorityClassSize': 9.0,
'NumberOfClasses': 6.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 214.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 9.0,
'NumberOfSymbolicFeatures': 1.0,
'cos... | glass | [
"RI",
"Na",
"Mg",
"Al",
"Si",
"K",
"Ca",
"Ba",
"Fe"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,266 |
267 | predictive_accuracy | accuracy_score | diabetes | **Author**: [Vincent Sigillito](vgs@aplcen.apl.jhu.edu)
**Source**: [Obtained from UCI](https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes)
**Please cite**: [UCI citation policy](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Pima Indians Diabetes Database
2. Sources:
(a) Origi... | {0: [0 - preg (numeric)],
1: [1 - plas (numeric)],
2: [2 - pres (numeric)],
3: [3 - skin (numeric)],
4: [4 - insu (numeric)],
5: [5 - mass (numeric)],
6: [6 - pedi (numeric)],
7: [7 - age (numeric)],
8: [8 - class (nominal)]} | {'MajorityClassSize': 500.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 268.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 9.0,
'NumberOfInstances': 768.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 8.0,
'NumberOfSymbolicFeatures': 1.0,
'c... | diabetes | [
"preg",
"plas",
"pres",
"skin",
"insu",
"mass",
"pedi",
"age"
] | [
false,
false,
false,
false,
false,
false,
false,
false
] | 1,267 |
282 | predictive_accuracy | accuracy_score | heart-statlog | **Author**:
**Source**: Unknown -
**Please cite**:
This database contains 13 attributes (which have been extracted from
a larger set of 75)
Attribute Information:
------------------------
-- 1. age
-- 2. sex
-- 3. chest pain type (4 values)
-... | {0: [0 - age (numeric)],
1: [1 - sex (numeric)],
2: [2 - chest (numeric)],
3: [3 - resting_blood_pressure (numeric)],
4: [4 - serum_cholestoral (numeric)],
5: [5 - fasting_blood_sugar (numeric)],
6: [6 - resting_electrocardiographic_results (numeric)],
7: [7 - maximum_heart_rate_achieved (numeric)],
8: [8 - exe... | {'MajorityClassSize': 150.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 120.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 270.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 13.0,
'NumberOfSymbolicFeatures': 1.0,
... | heart-statlog | [
"age",
"sex",
"chest",
"resting_blood_pressure",
"serum_cholestoral",
"fasting_blood_sugar",
"resting_electrocardiographic_results",
"maximum_heart_rate_achieved",
"exercise_induced_angina",
"oldpeak",
"slope",
"number_of_major_vessels",
"thal"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,268 |
277 | predictive_accuracy | accuracy_score | tae | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Teaching Assistant Evaluation
2. Sources:
(a) Collector: Wei-Yin Loh (Department of Statistics, UW-Madison)
(b) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
(b) Date: June 7, 1997
3. Past Usage:
1. Loh, W.-Y. & Shih, Y.-S... | {0: [0 - Whether_of_not_the_TA_is_a_native_English_speaker (nominal)],
1: [1 - Course_instructor (numeric)],
2: [2 - Course (numeric)],
3: [3 - Summer_or_regular_semester (nominal)],
4: [4 - Class_size (numeric)],
5: [5 - Class_attribute (nominal)]} | {'MajorityClassSize': 52.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 49.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 6.0,
'NumberOfInstances': 151.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3.0,
'NumberOfSymbolicFeatures': 3.0,
'cos... | tae | [
"Whether_of_not_the_TA_is_a_native_English_speaker",
"Course_instructor",
"Course",
"Summer_or_regular_semester",
"Class_size"
] | [
true,
false,
false,
true,
false
] | 1,269 |
260 | predictive_accuracy | accuracy_score | page-blocks | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title of Database: Blocks Classification
2. Sources:
(a) Donato Malerba
Dipartimento di Informatica
University of Bari
via Orabona 4
70126 Bari - Italy
phone: +39 - 80 - 5443269
fax: +39 - 80 - 5443196
... | {0: [0 - height (numeric)],
1: [1 - lenght (numeric)],
2: [2 - area (numeric)],
3: [3 - eccen (numeric)],
4: [4 - p_black (numeric)],
5: [5 - p_and (numeric)],
6: [6 - mean_tr (numeric)],
7: [7 - blackpix (numeric)],
8: [8 - blackand (numeric)],
9: [9 - wb_trans (numeric)],
10: [10 - class (nominal)]} | {'MajorityClassSize': 4913.0,
'MaxNominalAttDistinctValues': 5.0,
'MinorityClassSize': 28.0,
'NumberOfClasses': 5.0,
'NumberOfFeatures': 11.0,
'NumberOfInstances': 5473.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 10.0,
'NumberOfSymbolicFeatures': 1.0,
... | page-blocks | [
"height",
"lenght",
"area",
"eccen",
"p_black",
"p_and",
"mean_tr",
"blackpix",
"blackand",
"wb_trans"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,270 |
272 | predictive_accuracy | accuracy_score | haberman | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Haberman's Survival Data
2. Sources:
(a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
(b) Date: March 4, 1999
3. Past Usage:
1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear
Models, Proceedings of the 9th In... | {0: [0 - Age_of_patient_at_time_of_operation (numeric)],
1: [1 - Patients_year_of_operation (nominal)],
2: [2 - Number_of_positive_axillary_nodes_detected (numeric)],
3: [3 - Survival_status (nominal)]} | {'MajorityClassSize': 225.0,
'MaxNominalAttDistinctValues': 12.0,
'MinorityClassSize': 81.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 4.0,
'NumberOfInstances': 306.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2.0,
'NumberOfSymbolicFeatures': 2.0,
'c... | haberman | [
"Age_of_patient_at_time_of_operation",
"Patients_year_of_operation",
"Number_of_positive_axillary_nodes_detected"
] | [
false,
true,
false
] | 1,271 |
280 | predictive_accuracy | accuracy_score | heart-h | **Author**:
**Source**: Unknown -
**Please cite**:
Publication Request:
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
This file describes the contents of the heart-disease directory.
This directory contains 4 databases concerning heart disease diagnosis.
All attribu... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - chest_pain (nominal)],
3: [3 - trestbps (numeric)],
4: [4 - chol (numeric)],
5: [5 - fbs (nominal)],
6: [6 - restecg (nominal)],
7: [7 - thalach (numeric)],
8: [8 - exang (nominal)],
9: [9 - oldpeak (numeric)],
10: [10 - slope (nominal)],
11: [11 - ca ... | {'MajorityClassSize': 188.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 106.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 294.0,
'NumberOfInstancesWithMissingValues': 293.0,
'NumberOfMissingValues': 782.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 8.0... | heart-h | [
"age",
"sex",
"chest_pain",
"trestbps",
"chol",
"fbs",
"restecg",
"thalach",
"exang",
"oldpeak",
"slope",
"ca",
"thal"
] | [
false,
true,
true,
false,
false,
true,
true,
false,
true,
false,
true,
false,
true
] | 1,272 |
278 | predictive_accuracy | accuracy_score | heart-c | **Author**:
**Source**: Unknown -
**Please cite**:
Publication Request:
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
This file describes the contents of the heart-disease directory.
This directory contains 4 databases concerning heart disease diagnosis.
All attribu... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - cp (nominal)],
3: [3 - trestbps (numeric)],
4: [4 - chol (numeric)],
5: [5 - fbs (nominal)],
6: [6 - restecg (nominal)],
7: [7 - thalach (numeric)],
8: [8 - exang (nominal)],
9: [9 - oldpeak (numeric)],
10: [10 - slope (nominal)],
11: [11 - ca (numeric... | {'MajorityClassSize': 165.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 138.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 303.0,
'NumberOfInstancesWithMissingValues': 7.0,
'NumberOfMissingValues': 7.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 8.0,
'... | heart-c | [
"age",
"sex",
"cp",
"trestbps",
"chol",
"fbs",
"restecg",
"thalach",
"exang",
"oldpeak",
"slope",
"ca",
"thal"
] | [
false,
true,
true,
false,
false,
true,
true,
false,
true,
false,
true,
false,
true
] | 1,273 |
254 | predictive_accuracy | accuracy_score | mushroom | **Author**: [Jeff Schlimmer](Jeffrey.Schlimmer@a.gp.cs.cmu.edu)
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/mushroom) - 1981
**Please cite**: The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf
### Description
This dataset descri... | {0: [0 - cap-shape (nominal)],
1: [1 - cap-surface (nominal)],
2: [2 - cap-color (nominal)],
3: [3 - bruises%3F (nominal)],
4: [4 - odor (nominal)],
5: [5 - gill-attachment (nominal)],
6: [6 - gill-spacing (nominal)],
7: [7 - gill-size (nominal)],
8: [8 - gill-color (nominal)],
9: [9 - stalk-shape (nominal)],
... | {'MajorityClassSize': 4208.0,
'MaxNominalAttDistinctValues': 12.0,
'MinorityClassSize': 3916.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 23.0,
'NumberOfInstances': 8124.0,
'NumberOfInstancesWithMissingValues': 2480.0,
'NumberOfMissingValues': 2480.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures... | mushroom | [
"cap-shape",
"cap-surface",
"cap-color",
"bruises%3F",
"odor",
"gill-attachment",
"gill-spacing",
"gill-size",
"gill-color",
"stalk-shape",
"stalk-root",
"stalk-surface-above-ring",
"stalk-surface-below-ring",
"stalk-color-above-ring",
"stalk-color-below-ring",
"veil-type",
"veil-col... | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,274 |
363,716 | mean_absolute_error | mean_absolute_error | riboflavin | Dataset of riboflavin production by Bacillus subtilis containing n=71 observations of p=4088 predictors (gene expressions logarithmically scaled) and a one-dimensional response (riboflavin production rate logarithmically scaled). Data kindly provided by DSM (Switzerland). The response label is 'x' and other columns lab... | {0: [0 - x (numeric)],
1: [1 - AADK_at (numeric)],
2: [2 - AAPA_at (numeric)],
3: [3 - ABFA_at (numeric)],
4: [4 - ABH_at (numeric)],
5: [5 - ABNA_at (numeric)],
6: [6 - ABRB_at (numeric)],
7: [7 - ACCA_at (numeric)],
8: [8 - ACCB_at (numeric)],
9: [9 - ACCC_at (numeric)],
10: [10 - ACDA_at (numeric)],
11: [... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 4089.0,
'NumberOfInstances': 71.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 4089.0,
'NumberOfSymbolicFeatures': 0.0,
'... | riboflavin | [
"AADK_at",
"AAPA_at",
"ABFA_at",
"ABH_at",
"ABNA_at",
"ABRB_at",
"ACCA_at",
"ACCB_at",
"ACCC_at",
"ACDA_at",
"ACKA_at",
"ACOA_at",
"ACOB_at",
"ACOC_at",
"ACOL_at",
"ACOR_at",
"ACPA_at",
"ACSA_at",
"ACUA_at",
"ACUB_at",
"ACUC_at",
"ADAA_at",
"ADAB_at",
"ADDA_at",
"ADDB... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
f... | 1,275 |
266 | predictive_accuracy | accuracy_score | segment | **Author**: University of Massachusetts Vision Group, Carla Brodley
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/image+segmentation) - 1990
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Image Segmentation Data Set**
The instances were drawn randomly from a database of 7... | {0: [0 - region-centroid-col (numeric)],
1: [1 - region-centroid-row (numeric)],
2: [2 - region-pixel-count (numeric)],
3: [3 - short-line-density-5 (numeric)],
4: [4 - short-line-density-2 (numeric)],
5: [5 - vedge-mean (numeric)],
6: [6 - vegde-sd (numeric)],
7: [7 - hedge-mean (numeric)],
8: [8 - hedge-sd (n... | {'MajorityClassSize': 330.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 330.0,
'NumberOfClasses': 7.0,
'NumberOfFeatures': 20.0,
'NumberOfInstances': 2310.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 19.0,
'NumberOfSymbolicFeatures': 1.0,
... | segment | [
"region-centroid-col",
"region-centroid-row",
"region-pixel-count",
"short-line-density-5",
"short-line-density-2",
"vedge-mean",
"vegde-sd",
"hedge-mean",
"hedge-sd",
"intensity-mean",
"rawred-mean",
"rawblue-mean",
"rawgreen-mean",
"exred-mean",
"exblue-mean",
"exgreen-mean",
"valu... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,276 |
279 | predictive_accuracy | accuracy_score | tic-tac-toe | **Author**: David W. Aha
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Tic-Tac-Toe+Endgame) - 1991
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Tic-Tac-Toe Endgame database**
This database encodes the complete set of possible board configurations at the end of tic-t... | {0: [0 - top-left-square (nominal)],
1: [1 - top-middle-square (nominal)],
2: [2 - top-right-square (nominal)],
3: [3 - middle-left-square (nominal)],
4: [4 - middle-middle-square (nominal)],
5: [5 - middle-right-square (nominal)],
6: [6 - bottom-left-square (nominal)],
7: [7 - bottom-middle-square (nominal)],
... | {'MajorityClassSize': 626.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 332.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 958.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 10.0,
... | tic-tac-toe | [
"top-left-square",
"top-middle-square",
"top-right-square",
"middle-left-square",
"middle-middle-square",
"middle-right-square",
"bottom-left-square",
"bottom-middle-square",
"bottom-right-square"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,277 |
285 | predictive_accuracy | accuracy_score | vote | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: 1984 United States Congressional Voting Records Database
2. Source Information:
(a) Source: Congressional Quarterly Almanac, 98th Congress,
2nd session 1984, Volume XL: Congressional Quarterly Inc.
Wash... | {0: [0 - handicapped-infants (nominal)],
1: [1 - water-project-cost-sharing (nominal)],
2: [2 - adoption-of-the-budget-resolution (nominal)],
3: [3 - physician-fee-freeze (nominal)],
4: [4 - el-salvador-aid (nominal)],
5: [5 - religious-groups-in-schools (nominal)],
6: [6 - anti-satellite-test-ban (nominal)],
7:... | {'MajorityClassSize': 267.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 168.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 435.0,
'NumberOfInstancesWithMissingValues': 203.0,
'NumberOfMissingValues': 392.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 17.... | vote | [
"handicapped-infants",
"water-project-cost-sharing",
"adoption-of-the-budget-resolution",
"physician-fee-freeze",
"el-salvador-aid",
"religious-groups-in-schools",
"anti-satellite-test-ban",
"aid-to-nicaraguan-contras",
"mx-missile",
"immigration",
"synfuels-corporation-cutback",
"education-sp... | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,278 |
290 | predictive_accuracy | accuracy_score | zoo | **Author**: Richard S. Forsyth
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Zoo) - 5/15/1990
**Please cite**:
**Zoo database**
A simple database containing 17 Boolean-valued attributes describing animals. The "type" attribute appears to be the class attribute.
Notes:
* I find it unusual tha... | {0: [0 - animal (nominal)],
1: [1 - hair (nominal)],
2: [2 - feathers (nominal)],
3: [3 - eggs (nominal)],
4: [4 - milk (nominal)],
5: [5 - airborne (nominal)],
6: [6 - aquatic (nominal)],
7: [7 - predator (nominal)],
8: [8 - toothed (nominal)],
9: [9 - backbone (nominal)],
10: [10 - breathes (nominal)],
11:... | {'MajorityClassSize': 41.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 4.0,
'NumberOfClasses': 7.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 101.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 1.0,
'NumberOfSymbolicFeatures': 16.0,
'co... | zoo | [
"hair",
"feathers",
"eggs",
"milk",
"airborne",
"aquatic",
"predator",
"toothed",
"backbone",
"breathes",
"venomous",
"fins",
"legs",
"tail",
"domestic",
"catsize"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
true,
true,
true
] | 1,280 |
1,768 | predictive_accuracy | accuracy_score | labor | **Author**: Unknown
**Source**: Collective Barganing Review, Labour Canada
**Please cite**: https://archive.ics.uci.edu/ml/citation_policy.html
Date: Tue, 15 Nov 88 15:44:08 EST
From: stan <stan@csi2.UofO.EDU>
To: aha@ICS.UCI.EDU
1. Title: Final settlements in labor negotitions in Canadian industry
2. Source I... | {0: [0 - duration (numeric)],
1: [1 - wage-increase-first-year (numeric)],
2: [2 - wage-increase-second-year (numeric)],
3: [3 - wage-increase-third-year (numeric)],
4: [4 - cost-of-living-adjustment (nominal)],
5: [5 - working-hours (numeric)],
6: [6 - pension (nominal)],
7: [7 - standby-pay (numeric)],
8: [8 ... | {'MajorityClassSize': 37.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 20.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 57.0,
'NumberOfInstancesWithMissingValues': 56.0,
'NumberOfMissingValues': 326.0,
'NumberOfNumericFeatures': 8.0,
'NumberOfSymbolicFeatures': 9.0,
'... | labor | [
"duration",
"wage-increase-first-year",
"wage-increase-second-year",
"wage-increase-third-year",
"cost-of-living-adjustment",
"working-hours",
"pension",
"standby-pay",
"shift-differential",
"education-allowance",
"statutory-holidays",
"vacation",
"longterm-disability-assistance",
"contrib... | [
false,
false,
false,
false,
true,
false,
true,
false,
false,
true,
false,
true,
true,
true,
true,
true
] | 1,281 |
284 | predictive_accuracy | accuracy_score | hepatitis | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Hepatitis Domain
2. Sources:
(a) unknown
(b) Donor: G.Gong (Carnegie-Mellon University) via
Bojan Cestnik
Jozef Stefan Institute
Jamova 39
61000 Ljublja... | {0: [0 - AGE (numeric)],
1: [1 - SEX (nominal)],
2: [2 - STEROID (nominal)],
3: [3 - ANTIVIRALS (nominal)],
4: [4 - FATIGUE (nominal)],
5: [5 - MALAISE (nominal)],
6: [6 - ANOREXIA (nominal)],
7: [7 - LIVER_BIG (nominal)],
8: [8 - LIVER_FIRM (nominal)],
9: [9 - SPLEEN_PALPABLE (nominal)],
10: [10 - SPIDERS (n... | {'MajorityClassSize': 123.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 32.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 20.0,
'NumberOfInstances': 155.0,
'NumberOfInstancesWithMissingValues': 75.0,
'NumberOfMissingValues': 167.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 14.0,... | hepatitis | [
"AGE",
"SEX",
"STEROID",
"ANTIVIRALS",
"FATIGUE",
"MALAISE",
"ANOREXIA",
"LIVER_BIG",
"LIVER_FIRM",
"SPLEEN_PALPABLE",
"SPIDERS",
"ASCITES",
"VARICES",
"BILIRUBIN",
"ALK_PHOSPHATE",
"SGOT",
"ALBUMIN",
"PROTIME",
"HISTOLOGY"
] | [
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
false,
false,
false,
false,
true
] | 1,282 |
287 | predictive_accuracy | accuracy_score | ionosphere | **Author**: Space Physics Group, Applied Physics Laboratory, Johns Hopkins University. Donated by Vince Sigillito.
**Source**: [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/ionosphere)
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Johns Hopkins Universit... | {0: [0 - a01 (numeric)],
1: [1 - a02 (numeric)],
2: [2 - a03 (numeric)],
3: [3 - a04 (numeric)],
4: [4 - a05 (numeric)],
5: [5 - a06 (numeric)],
6: [6 - a07 (numeric)],
7: [7 - a08 (numeric)],
8: [8 - a09 (numeric)],
9: [9 - a10 (numeric)],
10: [10 - a11 (numeric)],
11: [11 - a12 (numeric)],
12: [12 - a13 (... | {'MajorityClassSize': 225.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 126.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 35.0,
'NumberOfInstances': 351.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 34.0,
'NumberOfSymbolicFeatures': 1.0,
... | ionosphere | [
"a01",
"a02",
"a03",
"a04",
"a05",
"a06",
"a07",
"a08",
"a09",
"a10",
"a11",
"a12",
"a13",
"a14",
"a15",
"a16",
"a17",
"a18",
"a19",
"a20",
"a21",
"a22",
"a23",
"a24",
"a25",
"a26",
"a27",
"a28",
"a29",
"a30",
"a31",
"a32",
"a33",
"a34"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,283 |
289 | predictive_accuracy | accuracy_score | iris | **Author**: R.A. Fisher
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Iris) - 1936 - Donated by Michael Marshall
**Please cite**:
**Iris Plants Database**
This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is ref... | {0: [0 - sepallength (numeric)],
1: [1 - sepalwidth (numeric)],
2: [2 - petallength (numeric)],
3: [3 - petalwidth (numeric)],
4: [4 - class (nominal)]} | {'MajorityClassSize': 50.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 50.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 5.0,
'NumberOfInstances': 150.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 4.0,
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'cos... | iris | [
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"sepalwidth",
"petallength",
"petalwidth"
] | [
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359,948 | root_mean_squared_error | root_mean_squared_error | SAT11-HAND-runtime-regression | source: http://www.cs.ubc.ca/labs/beta/Projects/SATzilla/
authors: L. Xu, F. Hutter, H. Hoos, K. Leyton-Brown
translator in coseal format: M. Lindauer with the help of Alexandre Frechette
the data do not distinguish between timeout, memout or crashes!
the status file will only have ok or timeout!
If features are "?", t... | {0: [0 - nvarsOrig (numeric)],
1: [1 - nclausesOrig (numeric)],
2: [2 - nvars (numeric)],
3: [3 - nclauses (numeric)],
4: [4 - reducedVars (numeric)],
5: [5 - reducedClauses (numeric)],
6: [6 - vars_clauses_ratio (numeric)],
7: [7 - POSNEG_RATIO_CLAUSE_mean (numeric)],
8: [8 - POSNEG_RATIO_CLAUSE_coeff_variatio... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': 15.0,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 117.0,
'NumberOfInstances': 4440.0,
'NumberOfInstancesWithMissingValues': 2715.0,
'NumberOfMissingValues': 27150.0,
'NumberOfNumericFeatures': 116.0,
'NumberOfSymbolicFeatures':... | SAT11-HAND-runtime-regression | [
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"POSNEG_RATIO_CLAUSE_coeff_variation",
"POSNEG_RATIO_CLAUSE_min",
"POSNEG_RATIO_CLAUSE_max",
"POSNEG_RATIO_CLAUSE_entropy",
"VCG_CLAUSE_mean",
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363,763 | mean_absolute_error | mean_absolute_error | LimeSoda_H.138_dataset | Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1... | {0: [0 - SOC_target (numeric)],
1: [1 - pH_target (numeric)],
2: [2 - Clay_target (numeric)],
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5: [5 - wn_5394 (numeric)],
6: [6 - wn_5392.1 (numeric)],
7: [7 - wn_5390.2 (numeric)],
8: [8 - wn_5388.2 (numeric)],
9: [9 - wn_5386.3 (numeric)],
10: [10 - ... | {'MajorityClassSize': nan,
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'NumberOfClasses': 0.0,
'NumberOfFeatures': 2492.0,
'NumberOfInstances': 138.0,
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'NumberOfNumericFeatures': 2492.0,
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... | LimeSoda_H.138_dataset | [
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1,771 | predictive_accuracy | accuracy_score | audiology | **Author**: Professor Jergen at Baylor College of Medicine
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Audiology+(Standardized))
**Please cite**: Bareiss, E. Ray, & Porter, Bruce (1987). Protos: An Exemplar-Based Learning Apprentice. In the Proceedings of the 4th International Workshop on Machine Learning... | {0: [0 - age_gt_60 (nominal)],
1: [1 - air (nominal)],
2: [2 - airBoneGap (nominal)],
3: [3 - ar_c (nominal)],
4: [4 - ar_u (nominal)],
5: [5 - bone (nominal)],
6: [6 - boneAbnormal (nominal)],
7: [7 - bser (nominal)],
8: [8 - history_buzzing (nominal)],
9: [9 - history_dizziness (nominal)],
10: [10 - history... | {'MajorityClassSize': 57.0,
'MaxNominalAttDistinctValues': 24.0,
'MinorityClassSize': 1.0,
'NumberOfClasses': 24.0,
'NumberOfFeatures': 70.0,
'NumberOfInstances': 226.0,
'NumberOfInstancesWithMissingValues': 222.0,
'NumberOfMissingValues': 317.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 70.0... | audiology | [
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"airBoneGap",
"ar_c",
"ar_u",
"bone",
"boneAbnormal",
"bser",
"history_buzzing",
"history_dizziness",
"history_fluctuating",
"history_fullness",
"history_heredity",
"history_nausea",
"history_noise",
"history_recruitment",
"history_ringing",
"history_roaring",
... | [
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true... | 1,287 |
283 | predictive_accuracy | accuracy_score | vehicle | **Author**: Dr. Pete Mowforth and Dr. Barry Shepherd
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Statlog+(Vehicle+Silhouettes))
**Please cite**: Siebert,JP. Turing Institute Research Memorandum TIRM-87-018 "Vehicle Recognition Using Rule Based Methods" (March 1987)
NAME
vehicle silhouettes
... | {0: [0 - COMPACTNESS (numeric)],
1: [1 - CIRCULARITY (numeric)],
2: [2 - DISTANCE_CIRCULARITY (numeric)],
3: [3 - RADIUS_RATIO (numeric)],
4: [4 - PR.AXIS_ASPECT_RATIO (numeric)],
5: [5 - MAX.LENGTH_ASPECT_RATIO (numeric)],
6: [6 - SCATTER_RATIO (numeric)],
7: [7 - ELONGATEDNESS (numeric)],
8: [8 - PR.AXIS_RECT... | {'MajorityClassSize': 218.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 199.0,
'NumberOfClasses': 4.0,
'NumberOfFeatures': 19.0,
'NumberOfInstances': 846.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 18.0,
'NumberOfSymbolicFeatures': 1.0,
... | vehicle | [
"COMPACTNESS",
"CIRCULARITY",
"DISTANCE_CIRCULARITY",
"RADIUS_RATIO",
"PR.AXIS_ASPECT_RATIO",
"MAX.LENGTH_ASPECT_RATIO",
"SCATTER_RATIO",
"ELONGATEDNESS",
"PR.AXIS_RECTANGULARITY",
"MAX.LENGTH_RECTANGULARITY",
"SCALED_VARIANCE_MAJOR",
"SCALED_VARIANCE_MINOR",
"SCALED_RADIUS_OF_GYRATION",
"... | [
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] | 1,288 |
1,777 | predictive_accuracy | accuracy_score | breast-cancer | **Author**:
**Source**: Unknown -
**Please cite**:
Citation Request:
This breast cancer domain was obtained from the University Medical Centre,
Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and
M. Soklic for providing the data. Please include this citation if you plan
... | {0: [0 - age (nominal)],
1: [1 - menopause (nominal)],
2: [2 - tumor-size (nominal)],
3: [3 - inv-nodes (nominal)],
4: [4 - node-caps (nominal)],
5: [5 - deg-malig (nominal)],
6: [6 - breast (nominal)],
7: [7 - breast-quad (nominal)],
8: [8 - irradiat (nominal)],
9: [9 - Class (nominal)]} | {'MajorityClassSize': 201.0,
'MaxNominalAttDistinctValues': 11.0,
'MinorityClassSize': 85.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 286.0,
'NumberOfInstancesWithMissingValues': 9.0,
'NumberOfMissingValues': 9.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 10.0,
... | breast-cancer | [
"age",
"menopause",
"tumor-size",
"inv-nodes",
"node-caps",
"deg-malig",
"breast",
"breast-quad",
"irradiat"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,289 |
1,774 | predictive_accuracy | accuracy_score | lymph | **Author**:
**Source**: Unknown -
**Please cite**:
Citation Request:
This lymphography domain was obtained from the University Medical Centre,
Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and
M. Soklic for providing the data. Please include this citation if you plan
... | {0: [0 - lymphatics (nominal)],
1: [1 - block_of_affere (nominal)],
2: [2 - bl_of_lymph_c (nominal)],
3: [3 - bl_of_lymph_s (nominal)],
4: [4 - by_pass (nominal)],
5: [5 - extravasates (nominal)],
6: [6 - regeneration_of (nominal)],
7: [7 - early_uptake_in (nominal)],
8: [8 - lym_nodes_dimin (numeric)],
9: [9 ... | {'MajorityClassSize': 81.0,
'MaxNominalAttDistinctValues': 8.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 4.0,
'NumberOfFeatures': 19.0,
'NumberOfInstances': 148.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3.0,
'NumberOfSymbolicFeatures': 16.0,
'co... | lymph | [
"lymphatics",
"block_of_affere",
"bl_of_lymph_c",
"bl_of_lymph_s",
"by_pass",
"extravasates",
"regeneration_of",
"early_uptake_in",
"lym_nodes_dimin",
"lym_nodes_enlar",
"changes_in_lym",
"defect_in_node",
"changes_in_node",
"changes_in_stru",
"special_forms",
"dislocation_of",
"excl... | [
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false,
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] | 1,290 |
246 | predictive_accuracy | accuracy_score | mfeat-karhunen | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Karhunen**
One of a set of 6 ... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 65.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 64.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-karhunen | [
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"att2",
"att3",
"att4",
"att5",
"att6",
"att7",
"att8",
"att9",
"att10",
"att11",
"att12",
"att13",
"att14",
"att15",
"att16",
"att17",
"att18",
"att19",
"att20",
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"att22",
"att23",
"att24",
"att25",
"att26",
"att27",
"att28",
"att29",
"att30... | [
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f... | 1,291 |
275 | predictive_accuracy | accuracy_score | splice | **Author**: Genbank. Donated by G. Towell, M. Noordewier, and J. Shavlik
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Splice-junction+Gene+Sequences))
**Please cite**: None
Primate splice-junction gene sequences (DNA) with associated imperfect domain theory.
Splice junctions are... | {0: [0 - Instance_name (nominal)],
1: [1 - attribute_1 (nominal)],
2: [2 - attribute_2 (nominal)],
3: [3 - attribute_3 (nominal)],
4: [4 - attribute_4 (nominal)],
5: [5 - attribute_5 (nominal)],
6: [6 - attribute_6 (nominal)],
7: [7 - attribute_7 (nominal)],
8: [8 - attribute_8 (nominal)],
9: [9 - attribute_9 ... | {'MajorityClassSize': 1655.0,
'MaxNominalAttDistinctValues': 6.0,
'MinorityClassSize': 767.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 61.0,
'NumberOfInstances': 3190.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 61.0,... | splice | [
"attribute_1",
"attribute_2",
"attribute_3",
"attribute_4",
"attribute_5",
"attribute_6",
"attribute_7",
"attribute_8",
"attribute_9",
"attribute_10",
"attribute_11",
"attribute_12",
"attribute_13",
"attribute_14",
"attribute_15",
"attribute_16",
"attribute_17",
"attribute_18",
"... | [
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1,779 | predictive_accuracy | accuracy_score | breast-w | **Author**: Dr. William H. Wolberg, University of Wisconsin
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(original)), [University of Wisconsin](http://pages.cs.wisc.edu/~olvi/uwmp/cancer.html) - 1995
**Please cite**: See below, plus [UCI](https://archive.ics.uci.edu/ml/citation_... | {0: [0 - Clump_Thickness (numeric)],
1: [1 - Cell_Size_Uniformity (numeric)],
2: [2 - Cell_Shape_Uniformity (numeric)],
3: [3 - Marginal_Adhesion (numeric)],
4: [4 - Single_Epi_Cell_Size (numeric)],
5: [5 - Bare_Nuclei (numeric)],
6: [6 - Bland_Chromatin (numeric)],
7: [7 - Normal_Nucleoli (numeric)],
8: [8 - M... | {'MajorityClassSize': 458.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 241.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 699.0,
'NumberOfInstancesWithMissingValues': 16.0,
'NumberOfMissingValues': 16.0,
'NumberOfNumericFeatures': 9.0,
'NumberOfSymbolicFeatures': 1.0,
... | breast-w | [
"Clump_Thickness",
"Cell_Size_Uniformity",
"Cell_Shape_Uniformity",
"Marginal_Adhesion",
"Single_Epi_Cell_Size",
"Bare_Nuclei",
"Bland_Chromatin",
"Normal_Nucleoli",
"Mitoses"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,293 |
271 | predictive_accuracy | accuracy_score | soybean | **Author**: R.S. Michalski and R.L. Chilausky (Donors: Ming Tan & Jeff Schlimmer)
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Soybean+(Large)) - 1988
**Please cite**: R.S. Michalski and R.L. Chilausky "Learning by Being Told and Learning from Examples: An Experimental Comparison of the Two Methods of ... | {0: [0 - date (nominal)],
1: [1 - plant-stand (nominal)],
2: [2 - precip (nominal)],
3: [3 - temp (nominal)],
4: [4 - hail (nominal)],
5: [5 - crop-hist (nominal)],
6: [6 - area-damaged (nominal)],
7: [7 - severity (nominal)],
8: [8 - seed-tmt (nominal)],
9: [9 - germination (nominal)],
10: [10 - plant-growth... | {'MajorityClassSize': 92.0,
'MaxNominalAttDistinctValues': 19.0,
'MinorityClassSize': 8.0,
'NumberOfClasses': 19.0,
'NumberOfFeatures': 36.0,
'NumberOfInstances': 683.0,
'NumberOfInstancesWithMissingValues': 121.0,
'NumberOfMissingValues': 2337.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 36.... | soybean | [
"date",
"plant-stand",
"precip",
"temp",
"hail",
"crop-hist",
"area-damaged",
"severity",
"seed-tmt",
"germination",
"plant-growth",
"leaves",
"leafspots-halo",
"leafspots-marg",
"leafspot-size",
"leaf-shread",
"leaf-malf",
"leaf-mild",
"stem",
"lodging",
"stem-cankers",
"c... | [
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true,
true,
true,
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true,
true,
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] | 1,294 |
1,787 | predictive_accuracy | accuracy_score | cmc | **Author**: [Tjen-Sien Lim](limt@stat.wisc.edu)
**Source**: [As obtained from UCI](https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice)
**Please cite**: [UCI citation](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Contraceptive Method Choice
2. Sources:
(a) Origin: This datase... | {0: [0 - Wifes_age (numeric)],
1: [1 - Wifes_education (nominal)],
2: [2 - Husbands_education (nominal)],
3: [3 - Number_of_children_ever_born (numeric)],
4: [4 - Wifes_religion (nominal)],
5: [5 - Wifes_now_working%3F (nominal)],
6: [6 - Husbands_occupation (nominal)],
7: [7 - Standard-of-living_index (nominal)... | {'MajorityClassSize': 629.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 333.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 1473.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2.0,
'NumberOfSymbolicFeatures': 8.0,
... | cmc | [
"Wifes_age",
"Wifes_education",
"Husbands_education",
"Number_of_children_ever_born",
"Wifes_religion",
"Wifes_now_working%3F",
"Husbands_occupation",
"Standard-of-living_index",
"Media_exposure"
] | [
false,
true,
true,
false,
true,
true,
true,
true,
true
] | 1,295 |
1,775 | predictive_accuracy | accuracy_score | balance-scale | **Author**: Siegler, R. S. (donated by Tim Hume)
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/balance+scale) - 1994
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Balance Scale Weight & Distance Database**
This data set was generated to model psychological experiment... | {0: [0 - left-weight (numeric)],
1: [1 - left-distance (numeric)],
2: [2 - right-weight (numeric)],
3: [3 - right-distance (numeric)],
4: [4 - class (nominal)]} | {'MajorityClassSize': 288.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 49.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 5.0,
'NumberOfInstances': 625.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 4.0,
'NumberOfSymbolicFeatures': 1.0,
'co... | balance-scale | [
"left-weight",
"left-distance",
"right-weight",
"right-distance"
] | [
false,
false,
false,
false
] | 1,296 |
252 | predictive_accuracy | accuracy_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
"att1",
"att2",
"att3",
"att4",
"att5",
"att6",
"att7",
"att8",
"att9",
"att10",
"att11",
"att12",
"att13",
"att14",
"att15",
"att16",
"att17",
"att18",
"att19",
"att20",
"att21",
"att22",
"att23",
"att24",
"att25",
"att26",
"att27",
"att28",
"att29",
"att30... | [
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false,
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f... | 1,297 |
1,773 | predictive_accuracy | accuracy_score | autos | **Author**: Jeffrey C. Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu)
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Automobile) - 1987
**Please cite**:
**1985 Auto Imports Database**
This data set consists of three types of entities: (a) the specification of an auto in terms of various characteris... | {0: [0 - normalized-losses (numeric)],
1: [1 - make (nominal)],
2: [2 - fuel-type (nominal)],
3: [3 - aspiration (nominal)],
4: [4 - num-of-doors (nominal)],
5: [5 - body-style (nominal)],
6: [6 - drive-wheels (nominal)],
7: [7 - engine-location (nominal)],
8: [8 - wheel-base (numeric)],
9: [9 - length (numeri... | {'MajorityClassSize': 67.0,
'MaxNominalAttDistinctValues': 22.0,
'MinorityClassSize': 3.0,
'NumberOfClasses': 6.0,
'NumberOfFeatures': 26.0,
'NumberOfInstances': 205.0,
'NumberOfInstancesWithMissingValues': 46.0,
'NumberOfMissingValues': 59.0,
'NumberOfNumericFeatures': 15.0,
'NumberOfSymbolicFeatures': 11.0,
... | autos | [
"normalized-losses",
"make",
"fuel-type",
"aspiration",
"num-of-doors",
"body-style",
"drive-wheels",
"engine-location",
"wheel-base",
"length",
"width",
"height",
"curb-weight",
"engine-type",
"num-of-cylinders",
"engine-size",
"fuel-system",
"bore",
"stroke",
"compression-rat... | [
false,
true,
true,
true,
true,
true,
true,
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false,
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false,
false,
true,
true,
false,
true,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,299 |
1,798 | predictive_accuracy | accuracy_score | postoperative-patient-data | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Postoperative Patient Data
2. Source Information:
-- Creators: Sharon Summers, School of Nursing, University of Kansas
Medical Center, Kansas City, KS 66160
Linda Woolery, School of Nursing, University of Mis... | {0: [0 - L-CORE (nominal)],
1: [1 - L-SURF (nominal)],
2: [2 - L-O2 (nominal)],
3: [3 - L-BP (nominal)],
4: [4 - SURF-STBL (nominal)],
5: [5 - CORE-STBL (nominal)],
6: [6 - BP-STBL (nominal)],
7: [7 - COMFORT (nominal)],
8: [8 - decision (nominal)]} | {'MajorityClassSize': 64.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 9.0,
'NumberOfInstances': 90.0,
'NumberOfInstancesWithMissingValues': 3.0,
'NumberOfMissingValues': 3.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 9.0,
'cost_... | postoperative-patient-data | [
"L-CORE",
"L-SURF",
"L-O2",
"L-BP",
"SURF-STBL",
"CORE-STBL",
"BP-STBL",
"COMFORT"
] | [
true,
true,
true,
true,
true,
true,
true,
true
] | 1,300 |
1,803 | predictive_accuracy | accuracy_score | sonar | **Author**:
**Source**: Unknown -
**Please cite**:
NAME: Sonar, Mines vs. Rocks
SUMMARY: This is the data set used by Gorman and Sejnowski in their study
of the classification of sonar signals using a neural network [1]. The
task is to train a network to discriminate between sonar signals bounced
off a... | {0: [0 - attribute_1 (numeric)],
1: [1 - attribute_2 (numeric)],
2: [2 - attribute_3 (numeric)],
3: [3 - attribute_4 (numeric)],
4: [4 - attribute_5 (numeric)],
5: [5 - attribute_6 (numeric)],
6: [6 - attribute_7 (numeric)],
7: [7 - attribute_8 (numeric)],
8: [8 - attribute_9 (numeric)],
9: [9 - attribute_10 (... | {'MajorityClassSize': 111.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 97.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 61.0,
'NumberOfInstances': 208.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 60.0,
'NumberOfSymbolicFeatures': 1.0,
'... | sonar | [
"attribute_1",
"attribute_2",
"attribute_3",
"attribute_4",
"attribute_5",
"attribute_6",
"attribute_7",
"attribute_8",
"attribute_9",
"attribute_10",
"attribute_11",
"attribute_12",
"attribute_13",
"attribute_14",
"attribute_15",
"attribute_16",
"attribute_17",
"attribute_18",
"... | [
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false,
false,
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false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
f... | 1,302 |
1,802 | predictive_accuracy | accuracy_score | ecoli | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Protein Localization Sites
2. Creator and Maintainer:
Kenta Nakai
Institue of Molecular and Cellular Biology
Osaka, University
1-3 Yamada-oka, Suita 565 Japan
nakai@imcb.osaka-u.ac.jp
http... | {0: [0 - mcg (numeric)],
1: [1 - gvh (numeric)],
2: [2 - lip (numeric)],
3: [3 - chg (numeric)],
4: [4 - aac (numeric)],
5: [5 - alm1 (numeric)],
6: [6 - alm2 (numeric)],
7: [7 - class (nominal)]} | {'MajorityClassSize': 143.0,
'MaxNominalAttDistinctValues': 8.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 8.0,
'NumberOfFeatures': 8.0,
'NumberOfInstances': 336.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 7.0,
'NumberOfSymbolicFeatures': 1.0,
'cos... | ecoli | [
"mcg",
"gvh",
"lip",
"chg",
"aac",
"alm1",
"alm2"
] | [
false,
false,
false,
false,
false,
false,
false
] | 1,303 |
1,769 | predictive_accuracy | accuracy_score | arrhythmia | **Author**: H. Altay Guvenir, Burak Acar, Haldun Muderrisoglu
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/arrhythmia)
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Cardiac Arrhythmia Database**
The aim is to determine the type of arrhythmia from the ECG recordings. ... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - height (numeric)],
3: [3 - weight (numeric)],
4: [4 - QRSduration (numeric)],
5: [5 - PRinterval (numeric)],
6: [6 - Q-Tinterval (numeric)],
7: [7 - Tinterval (numeric)],
8: [8 - Pinterval (numeric)],
9: [9 - QRS (numeric)],
10: [10 - T (numeric)],
11:... | {'MajorityClassSize': 245.0,
'MaxNominalAttDistinctValues': 13.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 13.0,
'NumberOfFeatures': 280.0,
'NumberOfInstances': 452.0,
'NumberOfInstancesWithMissingValues': 384.0,
'NumberOfMissingValues': 408.0,
'NumberOfNumericFeatures': 206.0,
'NumberOfSymbolicFeatures': ... | arrhythmia | [
"age",
"sex",
"height",
"weight",
"QRSduration",
"PRinterval",
"Q-Tinterval",
"Tinterval",
"Pinterval",
"QRS",
"T",
"P",
"QRST",
"J",
"heartrate",
"chDI_Qwave",
"chDI_Rwave",
"chDI_Swave",
"chDI_RPwave",
"chDI_SPwave",
"chDI_intrinsicReflecttions",
"chDI_RRwaveExists",
"c... | [
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tr... | 1,304 |
359,940 | root_mean_squared_error | root_mean_squared_error | yprop_4_1 | **Author**:
**Source**: Unknown - Date unknown
**Please cite**:
This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode).
The molecules and outputs are taken from the original studies (see below). The other... | {0: [0 - oz1 (numeric)],
1: [1 - oz2 (numeric)],
2: [2 - oz3 (numeric)],
3: [3 - oz4 (numeric)],
4: [4 - oz5 (numeric)],
5: [5 - oz6 (numeric)],
6: [6 - oz7 (numeric)],
7: [7 - oz8 (numeric)],
8: [8 - oz9 (numeric)],
9: [9 - oz10 (numeric)],
10: [10 - oz11 (numeric)],
11: [11 - oz12 (numeric)],
12: [12 - oz... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 252.0,
'NumberOfInstances': 8885.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 252.0,
'NumberOfSymbolicFeatures': 0.0,
'... | yprop_4_1 | [
"oz1",
"oz2",
"oz3",
"oz4",
"oz5",
"oz6",
"oz7",
"oz8",
"oz9",
"oz10",
"oz11",
"oz12",
"oz13",
"oz14",
"oz15",
"oz16",
"oz17",
"oz18",
"oz19",
"oz20",
"oz21",
"oz22",
"oz23",
"oz24",
"oz25",
"oz26",
"oz27",
"oz28",
"oz29",
"oz30",
"oz31",
"oz32",
"oz33... | [
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f... | 1,305 |
1,799 | predictive_accuracy | accuracy_score | dermatology | 1. Title: Dermatology Database
2. Source Information:
(a) Original owners:
-- 1. Nilsel Ilter, M.D., Ph.D.,
Gazi University,
School of Medicine
06510 Ankara, Turkey
Phone: +90 (312) 214 1080
-- 2. H. Altay Guvenir, PhD.,
Bilkent Univ... | {0: [0 - erythema (nominal)],
1: [1 - scaling (nominal)],
2: [2 - definite_borders (nominal)],
3: [3 - itching (nominal)],
4: [4 - koebner_phenomenon (nominal)],
5: [5 - polygonal_papules (nominal)],
6: [6 - follicular_papules (nominal)],
7: [7 - oral_mucosal_involvement (nominal)],
8: [8 - knee_and_elbow_invol... | {'MajorityClassSize': 112.0,
'MaxNominalAttDistinctValues': 6.0,
'MinorityClassSize': 20.0,
'NumberOfClasses': 6.0,
'NumberOfFeatures': 35.0,
'NumberOfInstances': 366.0,
'NumberOfInstancesWithMissingValues': 8.0,
'NumberOfMissingValues': 8.0,
'NumberOfNumericFeatures': 1.0,
'NumberOfSymbolicFeatures': 34.0,
'... | dermatology | [
"erythema",
"scaling",
"definite_borders",
"itching",
"koebner_phenomenon",
"polygonal_papules",
"follicular_papules",
"oral_mucosal_involvement",
"knee_and_elbow_involvement",
"scalp_involvement",
"family_history",
"melanin_incontinence",
"eosinophils_in_the_infiltrate",
"PNL_infiltrate",... | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
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true,
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true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false
] | 1,306 |
1,801 | predictive_accuracy | accuracy_score | diabetes | **Author**: [Vincent Sigillito](vgs@aplcen.apl.jhu.edu)
**Source**: [Obtained from UCI](https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes)
**Please cite**: [UCI citation policy](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Pima Indians Diabetes Database
2. Sources:
(a) Origi... | {0: [0 - preg (numeric)],
1: [1 - plas (numeric)],
2: [2 - pres (numeric)],
3: [3 - skin (numeric)],
4: [4 - insu (numeric)],
5: [5 - mass (numeric)],
6: [6 - pedi (numeric)],
7: [7 - age (numeric)],
8: [8 - class (nominal)]} | {'MajorityClassSize': 500.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 268.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 9.0,
'NumberOfInstances': 768.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 8.0,
'NumberOfSymbolicFeatures': 1.0,
'c... | diabetes | [
"preg",
"plas",
"pres",
"skin",
"insu",
"mass",
"pedi",
"age"
] | [
false,
false,
false,
false,
false,
false,
false,
false
] | 1,307 |
1,806 | predictive_accuracy | accuracy_score | haberman | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Haberman's Survival Data
2. Sources:
(a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
(b) Date: March 4, 1999
3. Past Usage:
1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear
Models, Proceedings of the 9th In... | {0: [0 - Age_of_patient_at_time_of_operation (numeric)],
1: [1 - Patients_year_of_operation (nominal)],
2: [2 - Number_of_positive_axillary_nodes_detected (numeric)],
3: [3 - Survival_status (nominal)]} | {'MajorityClassSize': 225.0,
'MaxNominalAttDistinctValues': 12.0,
'MinorityClassSize': 81.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 4.0,
'NumberOfInstances': 306.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 2.0,
'NumberOfSymbolicFeatures': 2.0,
'c... | haberman | [
"Age_of_patient_at_time_of_operation",
"Patients_year_of_operation",
"Number_of_positive_axillary_nodes_detected"
] | [
false,
true,
false
] | 1,308 |
1,793 | predictive_accuracy | accuracy_score | credit-approval | **Author**: Confidential - Donated by Ross Quinlan
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/credit+approval) - 1987
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Credit Approval**
This file concerns credit card applications. All attribute names and values have been... | {0: [0 - A1 (nominal)],
1: [1 - A2 (numeric)],
2: [2 - A3 (numeric)],
3: [3 - A4 (nominal)],
4: [4 - A5 (nominal)],
5: [5 - A6 (nominal)],
6: [6 - A7 (nominal)],
7: [7 - A8 (numeric)],
8: [8 - A9 (nominal)],
9: [9 - A10 (nominal)],
10: [10 - A11 (numeric)],
11: [11 - A12 (nominal)],
12: [12 - A13 (nominal)]... | {'MajorityClassSize': 383.0,
'MaxNominalAttDistinctValues': 14.0,
'MinorityClassSize': 307.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 16.0,
'NumberOfInstances': 690.0,
'NumberOfInstancesWithMissingValues': 37.0,
'NumberOfMissingValues': 67.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 10.0... | credit-approval | [
"A1",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
"A8",
"A9",
"A10",
"A11",
"A12",
"A13",
"A14",
"A15"
] | [
true,
false,
false,
true,
true,
true,
true,
false,
true,
true,
false,
true,
true,
false,
false
] | 1,309 |
1,767 | predictive_accuracy | accuracy_score | kr-vs-kp | Author: Alen Shapiro
Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Chess+(King-Rook+vs.+King-Pawn))
Please cite: [UCI citation policy](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title: Chess End-Game -- King+Rook versus King+Pawn on a7
(usually abbreviated KRKPA7). The pawn on a7 means it is one s... | {0: [0 - bkblk (nominal)],
1: [1 - bknwy (nominal)],
2: [2 - bkon8 (nominal)],
3: [3 - bkona (nominal)],
4: [4 - bkspr (nominal)],
5: [5 - bkxbq (nominal)],
6: [6 - bkxcr (nominal)],
7: [7 - bkxwp (nominal)],
8: [8 - blxwp (nominal)],
9: [9 - bxqsq (nominal)],
10: [10 - cntxt (nominal)],
11: [11 - dsopp (nom... | {'MajorityClassSize': 1669.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 1527.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 37.0,
'NumberOfInstances': 3196.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 37.0... | kr-vs-kp | [
"bkblk",
"bknwy",
"bkon8",
"bkona",
"bkspr",
"bkxbq",
"bkxcr",
"bkxwp",
"blxwp",
"bxqsq",
"cntxt",
"dsopp",
"dwipd",
"hdchk",
"katri",
"mulch",
"qxmsq",
"r2ar8",
"reskd",
"reskr",
"rimmx",
"rkxwp",
"rxmsq",
"simpl",
"skach",
"skewr",
"skrxp",
"spcop",
"stlmt",... | [
true,
true,
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true,
true,
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true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,310 |
1,811 | predictive_accuracy | accuracy_score | tae | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Teaching Assistant Evaluation
2. Sources:
(a) Collector: Wei-Yin Loh (Department of Statistics, UW-Madison)
(b) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
(b) Date: June 7, 1997
3. Past Usage:
1. Loh, W.-Y. & Shih, Y.-S... | {0: [0 - Whether_of_not_the_TA_is_a_native_English_speaker (nominal)],
1: [1 - Course_instructor (numeric)],
2: [2 - Course (numeric)],
3: [3 - Summer_or_regular_semester (nominal)],
4: [4 - Class_size (numeric)],
5: [5 - Class_attribute (nominal)]} | {'MajorityClassSize': 52.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 49.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 6.0,
'NumberOfInstances': 151.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3.0,
'NumberOfSymbolicFeatures': 3.0,
'cos... | tae | [
"Whether_of_not_the_TA_is_a_native_English_speaker",
"Course_instructor",
"Course",
"Summer_or_regular_semester",
"Class_size"
] | [
true,
false,
false,
true,
false
] | 1,311 |
1,795 | predictive_accuracy | accuracy_score | credit-g | **Author**: Dr. Hans Hofmann
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)) - 1994
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**German Credit dataset**
This dataset classifies people described by a set of attributes as good or bad credit... | {0: [0 - checking_status (nominal)],
1: [1 - duration (numeric)],
2: [2 - credit_history (nominal)],
3: [3 - purpose (nominal)],
4: [4 - credit_amount (numeric)],
5: [5 - savings_status (nominal)],
6: [6 - employment (nominal)],
7: [7 - installment_commitment (numeric)],
8: [8 - personal_status (nominal)],
9: ... | {'MajorityClassSize': 700.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 300.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 21.0,
'NumberOfInstances': 1000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 7.0,
'NumberOfSymbolicFeatures': 14.0,... | credit-g | [
"checking_status",
"duration",
"credit_history",
"purpose",
"credit_amount",
"savings_status",
"employment",
"installment_commitment",
"personal_status",
"other_parties",
"residence_since",
"property_magnitude",
"age",
"other_payment_plans",
"housing",
"existing_credits",
"job",
"n... | [
true,
false,
true,
true,
false,
true,
true,
false,
true,
true,
false,
true,
false,
true,
true,
false,
true,
false,
true,
true
] | 1,312 |
1,782 | predictive_accuracy | accuracy_score | mfeat-morphological | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Morphological**
One of a set ... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - class (nominal)]} | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 7.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 1.0,
... | mfeat-morphological | [
"att1",
"att2",
"att3",
"att4",
"att5",
"att6"
] | [
false,
false,
false,
false,
false,
false
] | 1,313 |
1,814 | predictive_accuracy | accuracy_score | heart-h | **Author**:
**Source**: Unknown -
**Please cite**:
Publication Request:
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
This file describes the contents of the heart-disease directory.
This directory contains 4 databases concerning heart disease diagnosis.
All attribu... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - chest_pain (nominal)],
3: [3 - trestbps (numeric)],
4: [4 - chol (numeric)],
5: [5 - fbs (nominal)],
6: [6 - restecg (nominal)],
7: [7 - thalach (numeric)],
8: [8 - exang (nominal)],
9: [9 - oldpeak (numeric)],
10: [10 - slope (nominal)],
11: [11 - ca ... | {'MajorityClassSize': 188.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 106.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 294.0,
'NumberOfInstancesWithMissingValues': 293.0,
'NumberOfMissingValues': 782.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 8.0... | heart-h | [
"age",
"sex",
"chest_pain",
"trestbps",
"chol",
"fbs",
"restecg",
"thalach",
"exang",
"oldpeak",
"slope",
"ca",
"thal"
] | [
false,
true,
true,
false,
false,
true,
true,
false,
true,
false,
true,
false,
true
] | 1,315 |
1,794 | predictive_accuracy | accuracy_score | page-blocks | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title of Database: Blocks Classification
2. Sources:
(a) Donato Malerba
Dipartimento di Informatica
University of Bari
via Orabona 4
70126 Bari - Italy
phone: +39 - 80 - 5443269
fax: +39 - 80 - 5443196
... | {0: [0 - height (numeric)],
1: [1 - lenght (numeric)],
2: [2 - area (numeric)],
3: [3 - eccen (numeric)],
4: [4 - p_black (numeric)],
5: [5 - p_and (numeric)],
6: [6 - mean_tr (numeric)],
7: [7 - blackpix (numeric)],
8: [8 - blackand (numeric)],
9: [9 - wb_trans (numeric)],
10: [10 - class (nominal)]} | {'MajorityClassSize': 4913.0,
'MaxNominalAttDistinctValues': 5.0,
'MinorityClassSize': 28.0,
'NumberOfClasses': 5.0,
'NumberOfFeatures': 11.0,
'NumberOfInstances': 5473.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 10.0,
'NumberOfSymbolicFeatures': 1.0,
... | page-blocks | [
"height",
"lenght",
"area",
"eccen",
"p_black",
"p_and",
"mean_tr",
"blackpix",
"blackand",
"wb_trans"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,316 |
363,371 | root_mean_squared_error | root_mean_squared_error | google_qa_question_type_reason_explanation | Given a question and an answer (from the Crowdsource team at Google) as well as additional
category features, predict the (subjective) type of the question in relation to the answer. These data
stem from the same source as qaa, where the different labels were both prediction targets in the
original (multi-l... | {0: [0 - qa_id (numeric)],
1: [1 - question_title (string)],
2: [2 - question_body (string)],
3: [3 - question_user_name (string)],
4: [4 - question_user_page (string)],
5: [5 - answer (string)],
6: [6 - answer_user_name (string)],
7: [7 - answer_user_page (string)],
8: [8 - url (string)],
9: [9 - category (st... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 41.0,
'NumberOfInstances': 4863.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 31.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | google_qa_question_type_reason_explanation | [
"qa_id",
"question_title",
"question_body",
"question_user_name",
"question_user_page",
"answer",
"answer_user_name",
"answer_user_page",
"url",
"category",
"host",
"question_asker_intent_understanding",
"question_body_critical",
"question_conversational",
"question_expect_short_answer",... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
f... | 1,317 |
1,804 | predictive_accuracy | accuracy_score | glass | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Glass Identification Database
2. Sources:
(a) Creator: B. German
-- Central Research Establishment
Home Office Forensic Science Service
Aldermaston, Reading, Berkshire RG7 4PN
(b) Donor: Vina Spiehler, P... | {0: [0 - RI (numeric)],
1: [1 - Na (numeric)],
2: [2 - Mg (numeric)],
3: [3 - Al (numeric)],
4: [4 - Si (numeric)],
5: [5 - K (numeric)],
6: [6 - Ca (numeric)],
7: [7 - Ba (numeric)],
8: [8 - Fe (numeric)],
9: [9 - Type (nominal)]} | {'MajorityClassSize': 76.0,
'MaxNominalAttDistinctValues': 6.0,
'MinorityClassSize': 9.0,
'NumberOfClasses': 6.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 214.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 9.0,
'NumberOfSymbolicFeatures': 1.0,
'cos... | glass | [
"RI",
"Na",
"Mg",
"Al",
"Si",
"K",
"Ca",
"Ba",
"Fe"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,318 |
363,370 | root_mean_squared_error | root_mean_squared_error | google_qa_answer_type_reason_explanation | Given a question and an answer (from the Crowdsource team at Google) as well as an additional
category feature, predict the (subjective) type of the answer in relation to the question. Representing
a predominantly NLP task that requires deep language understanding (though the most accurate
models must also ... | {0: [0 - qa_id (numeric)],
1: [1 - question_title (string)],
2: [2 - question_body (string)],
3: [3 - question_user_name (string)],
4: [4 - question_user_page (string)],
5: [5 - answer (string)],
6: [6 - answer_user_name (string)],
7: [7 - answer_user_page (string)],
8: [8 - url (string)],
9: [9 - category (st... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 41.0,
'NumberOfInstances': 4863.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 31.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | google_qa_answer_type_reason_explanation | [
"qa_id",
"question_title",
"question_body",
"question_user_name",
"question_user_page",
"answer",
"answer_user_name",
"answer_user_page",
"url",
"category",
"host",
"question_asker_intent_understanding",
"question_body_critical",
"question_conversational",
"question_expect_short_answer",... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
f... | 1,319 |
1,812 | predictive_accuracy | accuracy_score | heart-c | **Author**:
**Source**: Unknown -
**Please cite**:
Publication Request:
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
This file describes the contents of the heart-disease directory.
This directory contains 4 databases concerning heart disease diagnosis.
All attribu... | {0: [0 - age (numeric)],
1: [1 - sex (nominal)],
2: [2 - cp (nominal)],
3: [3 - trestbps (numeric)],
4: [4 - chol (numeric)],
5: [5 - fbs (nominal)],
6: [6 - restecg (nominal)],
7: [7 - thalach (numeric)],
8: [8 - exang (nominal)],
9: [9 - oldpeak (numeric)],
10: [10 - slope (nominal)],
11: [11 - ca (numeric... | {'MajorityClassSize': 165.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 138.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 303.0,
'NumberOfInstancesWithMissingValues': 7.0,
'NumberOfMissingValues': 7.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 8.0,
'... | heart-c | [
"age",
"sex",
"cp",
"trestbps",
"chol",
"fbs",
"restecg",
"thalach",
"exang",
"oldpeak",
"slope",
"ca",
"thal"
] | [
false,
true,
true,
false,
false,
true,
true,
false,
true,
false,
true,
false,
true
] | 1,320 |
1,813 | predictive_accuracy | accuracy_score | tic-tac-toe | **Author**: David W. Aha
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Tic-Tac-Toe+Endgame) - 1991
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Tic-Tac-Toe Endgame database**
This database encodes the complete set of possible board configurations at the end of tic-t... | {0: [0 - top-left-square (nominal)],
1: [1 - top-middle-square (nominal)],
2: [2 - top-right-square (nominal)],
3: [3 - middle-left-square (nominal)],
4: [4 - middle-middle-square (nominal)],
5: [5 - middle-right-square (nominal)],
6: [6 - bottom-left-square (nominal)],
7: [7 - bottom-middle-square (nominal)],
... | {'MajorityClassSize': 626.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 332.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 10.0,
'NumberOfInstances': 958.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 10.0,
... | tic-tac-toe | [
"top-left-square",
"top-middle-square",
"top-right-square",
"middle-left-square",
"middle-middle-square",
"middle-right-square",
"bottom-left-square",
"bottom-middle-square",
"bottom-right-square"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,321 |
1,816 | predictive_accuracy | accuracy_score | heart-statlog | **Author**:
**Source**: Unknown -
**Please cite**:
This database contains 13 attributes (which have been extracted from
a larger set of 75)
Attribute Information:
------------------------
-- 1. age
-- 2. sex
-- 3. chest pain type (4 values)
-... | {0: [0 - age (numeric)],
1: [1 - sex (numeric)],
2: [2 - chest (numeric)],
3: [3 - resting_blood_pressure (numeric)],
4: [4 - serum_cholestoral (numeric)],
5: [5 - fasting_blood_sugar (numeric)],
6: [6 - resting_electrocardiographic_results (numeric)],
7: [7 - maximum_heart_rate_achieved (numeric)],
8: [8 - exe... | {'MajorityClassSize': 150.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 120.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 14.0,
'NumberOfInstances': 270.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 13.0,
'NumberOfSymbolicFeatures': 1.0,
... | heart-statlog | [
"age",
"sex",
"chest",
"resting_blood_pressure",
"serum_cholestoral",
"fasting_blood_sugar",
"resting_electrocardiographic_results",
"maximum_heart_rate_achieved",
"exercise_induced_angina",
"oldpeak",
"slope",
"number_of_major_vessels",
"thal"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,322 |
1,766 | predictive_accuracy | accuracy_score | anneal | **Author**: Unknown. Donated by David Sterling and Wray Buntine
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Annealing) - 1990
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
The original Annealing dataset from UCI. The exact meaning of the features and classes is lar... | {0: [0 - family (nominal)],
1: [1 - product-type (nominal)],
2: [2 - steel (nominal)],
3: [3 - carbon (numeric)],
4: [4 - hardness (numeric)],
5: [5 - temper_rolling (nominal)],
6: [6 - condition (nominal)],
7: [7 - formability (nominal)],
8: [8 - strength (numeric)],
9: [9 - non-ageing (nominal)],
10: [10 - ... | {'MajorityClassSize': 684.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 8.0,
'NumberOfClasses': 5.0,
'NumberOfFeatures': 39.0,
'NumberOfInstances': 898.0,
'NumberOfInstancesWithMissingValues': 898.0,
'NumberOfMissingValues': 22175.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 33.... | anneal | [
"family",
"product-type",
"steel",
"carbon",
"hardness",
"temper_rolling",
"condition",
"formability",
"strength",
"non-ageing",
"surface-finish",
"surface-quality",
"enamelability",
"bc",
"bf",
"bt",
"bw%2Fme",
"bl",
"m",
"chrom",
"phos",
"cbond",
"marvi",
"exptl",
"... | [
true,
true,
true,
false,
false,
true,
true,
true,
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
false,
false,
true,
true,
true
] | 1,323 |
1,818 | predictive_accuracy | accuracy_score | hepatitis | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: Hepatitis Domain
2. Sources:
(a) unknown
(b) Donor: G.Gong (Carnegie-Mellon University) via
Bojan Cestnik
Jozef Stefan Institute
Jamova 39
61000 Ljublja... | {0: [0 - AGE (numeric)],
1: [1 - SEX (nominal)],
2: [2 - STEROID (nominal)],
3: [3 - ANTIVIRALS (nominal)],
4: [4 - FATIGUE (nominal)],
5: [5 - MALAISE (nominal)],
6: [6 - ANOREXIA (nominal)],
7: [7 - LIVER_BIG (nominal)],
8: [8 - LIVER_FIRM (nominal)],
9: [9 - SPLEEN_PALPABLE (nominal)],
10: [10 - SPIDERS (n... | {'MajorityClassSize': 123.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 32.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 20.0,
'NumberOfInstances': 155.0,
'NumberOfInstancesWithMissingValues': 75.0,
'NumberOfMissingValues': 167.0,
'NumberOfNumericFeatures': 6.0,
'NumberOfSymbolicFeatures': 14.0,... | hepatitis | [
"AGE",
"SEX",
"STEROID",
"ANTIVIRALS",
"FATIGUE",
"MALAISE",
"ANOREXIA",
"LIVER_BIG",
"LIVER_FIRM",
"SPLEEN_PALPABLE",
"SPIDERS",
"ASCITES",
"VARICES",
"BILIRUBIN",
"ALK_PHOSPHATE",
"SGOT",
"ALBUMIN",
"PROTIME",
"HISTOLOGY"
] | [
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
false,
false,
false,
false,
true
] | 1,325 |
1,800 | predictive_accuracy | accuracy_score | segment | **Author**: University of Massachusetts Vision Group, Carla Brodley
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/image+segmentation) - 1990
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Image Segmentation Data Set**
The instances were drawn randomly from a database of 7... | {0: [0 - region-centroid-col (numeric)],
1: [1 - region-centroid-row (numeric)],
2: [2 - region-pixel-count (numeric)],
3: [3 - short-line-density-5 (numeric)],
4: [4 - short-line-density-2 (numeric)],
5: [5 - vedge-mean (numeric)],
6: [6 - vegde-sd (numeric)],
7: [7 - hedge-mean (numeric)],
8: [8 - hedge-sd (n... | {'MajorityClassSize': 330.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 330.0,
'NumberOfClasses': 7.0,
'NumberOfFeatures': 20.0,
'NumberOfInstances': 2310.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 19.0,
'NumberOfSymbolicFeatures': 1.0,
... | segment | [
"region-centroid-col",
"region-centroid-row",
"region-pixel-count",
"short-line-density-5",
"short-line-density-2",
"vedge-mean",
"vegde-sd",
"hedge-mean",
"hedge-sd",
"intensity-mean",
"rawred-mean",
"rawblue-mean",
"rawgreen-mean",
"exred-mean",
"exblue-mean",
"exgreen-mean",
"valu... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,326 |
363,593 | root_mean_squared_error | root_mean_squared_error | google_qa_answer_type_reason_explanation | Given a question and an answer (from the Crowdsource team at Google) as well as an additional
category feature, predict the (subjective) type of the answer in relation to the question. Representing
a predominantly NLP task that requires deep language understanding (though the most accurate
models must also ... | {0: [0 - question_title (string)],
1: [1 - question_body (string)],
2: [2 - question_user_name (string)],
3: [3 - question_user_page (string)],
4: [4 - answer (string)],
5: [5 - answer_user_name (string)],
6: [6 - answer_user_page (string)],
7: [7 - url (string)],
8: [8 - category (string)],
9: [9 - host (stri... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 40.0,
'NumberOfInstances': 4863.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 30.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | google_qa_answer_type_reason_explanation | [
"question_title",
"question_body",
"question_user_name",
"question_user_page",
"answer",
"answer_user_name",
"answer_user_page",
"url",
"category",
"host",
"question_asker_intent_understanding",
"question_body_critical",
"question_conversational",
"question_expect_short_answer",
"questio... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
f... | 1,327 |
1,821 | predictive_accuracy | accuracy_score | ionosphere | **Author**: Space Physics Group, Applied Physics Laboratory, Johns Hopkins University. Donated by Vince Sigillito.
**Source**: [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/ionosphere)
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Johns Hopkins Universit... | {0: [0 - a01 (numeric)],
1: [1 - a02 (numeric)],
2: [2 - a03 (numeric)],
3: [3 - a04 (numeric)],
4: [4 - a05 (numeric)],
5: [5 - a06 (numeric)],
6: [6 - a07 (numeric)],
7: [7 - a08 (numeric)],
8: [8 - a09 (numeric)],
9: [9 - a10 (numeric)],
10: [10 - a11 (numeric)],
11: [11 - a12 (numeric)],
12: [12 - a13 (... | {'MajorityClassSize': 225.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 126.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 35.0,
'NumberOfInstances': 351.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 34.0,
'NumberOfSymbolicFeatures': 1.0,
... | ionosphere | [
"a01",
"a02",
"a03",
"a04",
"a05",
"a06",
"a07",
"a08",
"a09",
"a10",
"a11",
"a12",
"a13",
"a14",
"a15",
"a16",
"a17",
"a18",
"a19",
"a20",
"a21",
"a22",
"a23",
"a24",
"a25",
"a26",
"a27",
"a28",
"a29",
"a30",
"a31",
"a32",
"a33",
"a34"
] | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | 1,328 |
1,819 | predictive_accuracy | accuracy_score | vote | **Author**:
**Source**: Unknown -
**Please cite**:
1. Title: 1984 United States Congressional Voting Records Database
2. Source Information:
(a) Source: Congressional Quarterly Almanac, 98th Congress,
2nd session 1984, Volume XL: Congressional Quarterly Inc.
Wash... | {0: [0 - handicapped-infants (nominal)],
1: [1 - water-project-cost-sharing (nominal)],
2: [2 - adoption-of-the-budget-resolution (nominal)],
3: [3 - physician-fee-freeze (nominal)],
4: [4 - el-salvador-aid (nominal)],
5: [5 - religious-groups-in-schools (nominal)],
6: [6 - anti-satellite-test-ban (nominal)],
7:... | {'MajorityClassSize': 267.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 168.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 435.0,
'NumberOfInstancesWithMissingValues': 203.0,
'NumberOfMissingValues': 392.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 17.... | vote | [
"handicapped-infants",
"water-project-cost-sharing",
"adoption-of-the-budget-resolution",
"physician-fee-freeze",
"el-salvador-aid",
"religious-groups-in-schools",
"anti-satellite-test-ban",
"aid-to-nicaraguan-contras",
"mx-missile",
"immigration",
"synfuels-corporation-cutback",
"education-sp... | [
true,
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true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,329 |
258 | predictive_accuracy | accuracy_score | optdigits | **Author**: E. Alpaydin, C. Kaynak
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/optical+recognition+of+handwritten+digits)
**Please cite**: [UCI citation policy](https://archive.ics.uci.edu/ml/citation_policy.html)
1. Title of Database: Optical Recognition of Handwritten Digits
2. Source:
E. Alp... | {0: [0 - input1 (numeric)],
1: [1 - input2 (numeric)],
2: [2 - input3 (numeric)],
3: [3 - input4 (numeric)],
4: [4 - input5 (numeric)],
5: [5 - input6 (numeric)],
6: [6 - input7 (numeric)],
7: [7 - input8 (numeric)],
8: [8 - input9 (numeric)],
9: [9 - input10 (numeric)],
10: [10 - input11 (numeric)],
11: [11... | {'MajorityClassSize': 572.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 554.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 65.0,
'NumberOfInstances': 5620.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 64.0,
'NumberOfSymbolicFeatures': 1.0... | optdigits | [
"input1",
"input2",
"input3",
"input4",
"input5",
"input6",
"input7",
"input8",
"input9",
"input10",
"input11",
"input12",
"input13",
"input14",
"input15",
"input16",
"input17",
"input18",
"input19",
"input20",
"input21",
"input22",
"input23",
"input24",
"input25",
... | [
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f... | 1,330 |
1,823 | predictive_accuracy | accuracy_score | iris | **Author**: R.A. Fisher
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Iris) - 1936 - Donated by Michael Marshall
**Please cite**:
**Iris Plants Database**
This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is ref... | {0: [0 - sepallength (numeric)],
1: [1 - sepalwidth (numeric)],
2: [2 - petallength (numeric)],
3: [3 - petalwidth (numeric)],
4: [4 - class (nominal)]} | {'MajorityClassSize': 50.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 50.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 5.0,
'NumberOfInstances': 150.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 4.0,
'NumberOfSymbolicFeatures': 1.0,
'cos... | iris | [
"sepallength",
"sepalwidth",
"petallength",
"petalwidth"
] | [
false,
false,
false,
false
] | 1,331 |
1,824 | predictive_accuracy | accuracy_score | zoo | **Author**: Richard S. Forsyth
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Zoo) - 5/15/1990
**Please cite**:
**Zoo database**
A simple database containing 17 Boolean-valued attributes describing animals. The "type" attribute appears to be the class attribute.
Notes:
* I find it unusual tha... | {0: [0 - animal (nominal)],
1: [1 - hair (nominal)],
2: [2 - feathers (nominal)],
3: [3 - eggs (nominal)],
4: [4 - milk (nominal)],
5: [5 - airborne (nominal)],
6: [6 - aquatic (nominal)],
7: [7 - predator (nominal)],
8: [8 - toothed (nominal)],
9: [9 - backbone (nominal)],
10: [10 - breathes (nominal)],
11:... | {'MajorityClassSize': 41.0,
'MaxNominalAttDistinctValues': 7.0,
'MinorityClassSize': 4.0,
'NumberOfClasses': 7.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 101.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 1.0,
'NumberOfSymbolicFeatures': 16.0,
'co... | zoo | [
"hair",
"feathers",
"eggs",
"milk",
"airborne",
"aquatic",
"predator",
"toothed",
"backbone",
"breathes",
"venomous",
"fins",
"legs",
"tail",
"domestic",
"catsize"
] | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
true,
true,
true
] | 1,332 |
1,786 | predictive_accuracy | accuracy_score | mfeat-zernike | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Zernike**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 48.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 47.0,
'NumberOfSymbolicFeatures': 1.0... | mfeat-zernike | [
"att1",
"att2",
"att3",
"att4",
"att5",
"att6",
"att7",
"att8",
"att9",
"att10",
"att11",
"att12",
"att13",
"att14",
"att15",
"att16",
"att17",
"att18",
"att19",
"att20",
"att21",
"att22",
"att23",
"att24",
"att25",
"att26",
"att27",
"att28",
"att29",
"att30... | [
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f... | 1,334 |
288 | predictive_accuracy | accuracy_score | waveform-5000 | **Author**: Breiman,L., Friedman,J.H., Olshen,R.A., & Stone,C.J.
**Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/waveform+database+generator+(version+2)) - 1988
**Please cite**: [UCI](http://archive.ics.uci.edu/ml/citation_policy.html)
**Waveform Database Generator**
Generator generating 3 classes o... | {0: [0 - x1 (numeric)],
1: [1 - x2 (numeric)],
2: [2 - x3 (numeric)],
3: [3 - x4 (numeric)],
4: [4 - x5 (numeric)],
5: [5 - x6 (numeric)],
6: [6 - x7 (numeric)],
7: [7 - x8 (numeric)],
8: [8 - x9 (numeric)],
9: [9 - x10 (numeric)],
10: [10 - x11 (numeric)],
11: [11 - x12 (numeric)],
12: [12 - x13 (numeric)]... | {'MajorityClassSize': 1692.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 1653.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 41.0,
'NumberOfInstances': 5000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 40.0,
'NumberOfSymbolicFeatures': 1.0... | waveform-5000 | [
"x1",
"x2",
"x3",
"x4",
"x5",
"x6",
"x7",
"x8",
"x9",
"x10",
"x11",
"x12",
"x13",
"x14",
"x15",
"x16",
"x17",
"x18",
"x19",
"x20",
"x21",
"x22",
"x23",
"x24",
"x25",
"x26",
"x27",
"x28",
"x29",
"x30",
"x31",
"x32",
"x33",
"x34",
"x35",
"x36",
"... | [
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f... | 1,335 |
1,788 | predictive_accuracy | accuracy_score | mushroom | **Author**: [Jeff Schlimmer](Jeffrey.Schlimmer@a.gp.cs.cmu.edu)
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/mushroom) - 1981
**Please cite**: The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf
### Description
This dataset descri... | {0: [0 - cap-shape (nominal)],
1: [1 - cap-surface (nominal)],
2: [2 - cap-color (nominal)],
3: [3 - bruises%3F (nominal)],
4: [4 - odor (nominal)],
5: [5 - gill-attachment (nominal)],
6: [6 - gill-spacing (nominal)],
7: [7 - gill-size (nominal)],
8: [8 - gill-color (nominal)],
9: [9 - stalk-shape (nominal)],
... | {'MajorityClassSize': 4208.0,
'MaxNominalAttDistinctValues': 12.0,
'MinorityClassSize': 3916.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 23.0,
'NumberOfInstances': 8124.0,
'NumberOfInstancesWithMissingValues': 2480.0,
'NumberOfMissingValues': 2480.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures... | mushroom | [
"cap-shape",
"cap-surface",
"cap-color",
"bruises%3F",
"odor",
"gill-attachment",
"gill-spacing",
"gill-size",
"gill-color",
"stalk-shape",
"stalk-root",
"stalk-surface-above-ring",
"stalk-surface-below-ring",
"stalk-color-above-ring",
"stalk-color-below-ring",
"veil-type",
"veil-col... | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,336 |
1,884 | predictive_accuracy | accuracy_score | labor | **Author**: Unknown
**Source**: Collective Barganing Review, Labour Canada
**Please cite**: https://archive.ics.uci.edu/ml/citation_policy.html
Date: Tue, 15 Nov 88 15:44:08 EST
From: stan <stan@csi2.UofO.EDU>
To: aha@ICS.UCI.EDU
1. Title: Final settlements in labor negotitions in Canadian industry
2. Source I... | {0: [0 - duration (numeric)],
1: [1 - wage-increase-first-year (numeric)],
2: [2 - wage-increase-second-year (numeric)],
3: [3 - wage-increase-third-year (numeric)],
4: [4 - cost-of-living-adjustment (nominal)],
5: [5 - working-hours (numeric)],
6: [6 - pension (nominal)],
7: [7 - standby-pay (numeric)],
8: [8 ... | {'MajorityClassSize': 37.0,
'MaxNominalAttDistinctValues': 3.0,
'MinorityClassSize': 20.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 17.0,
'NumberOfInstances': 57.0,
'NumberOfInstancesWithMissingValues': 56.0,
'NumberOfMissingValues': 326.0,
'NumberOfNumericFeatures': 8.0,
'NumberOfSymbolicFeatures': 9.0,
'... | labor | [
"duration",
"wage-increase-first-year",
"wage-increase-second-year",
"wage-increase-third-year",
"cost-of-living-adjustment",
"working-hours",
"pension",
"standby-pay",
"shift-differential",
"education-allowance",
"statutory-holidays",
"vacation",
"longterm-disability-assistance",
"contrib... | [
false,
false,
false,
false,
true,
false,
true,
false,
false,
true,
false,
true,
true,
true,
true,
true
] | 1,337 |
1,817 | predictive_accuracy | accuracy_score | vehicle | **Author**: Dr. Pete Mowforth and Dr. Barry Shepherd
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Statlog+(Vehicle+Silhouettes))
**Please cite**: Siebert,JP. Turing Institute Research Memorandum TIRM-87-018 "Vehicle Recognition Using Rule Based Methods" (March 1987)
NAME
vehicle silhouettes
... | {0: [0 - COMPACTNESS (numeric)],
1: [1 - CIRCULARITY (numeric)],
2: [2 - DISTANCE_CIRCULARITY (numeric)],
3: [3 - RADIUS_RATIO (numeric)],
4: [4 - PR.AXIS_ASPECT_RATIO (numeric)],
5: [5 - MAX.LENGTH_ASPECT_RATIO (numeric)],
6: [6 - SCATTER_RATIO (numeric)],
7: [7 - ELONGATEDNESS (numeric)],
8: [8 - PR.AXIS_RECT... | {'MajorityClassSize': 218.0,
'MaxNominalAttDistinctValues': 4.0,
'MinorityClassSize': 199.0,
'NumberOfClasses': 4.0,
'NumberOfFeatures': 19.0,
'NumberOfInstances': 846.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 18.0,
'NumberOfSymbolicFeatures': 1.0,
... | vehicle | [
"COMPACTNESS",
"CIRCULARITY",
"DISTANCE_CIRCULARITY",
"RADIUS_RATIO",
"PR.AXIS_ASPECT_RATIO",
"MAX.LENGTH_ASPECT_RATIO",
"SCATTER_RATIO",
"ELONGATEDNESS",
"PR.AXIS_RECTANGULARITY",
"MAX.LENGTH_RECTANGULARITY",
"SCALED_VARIANCE_MAJOR",
"SCALED_VARIANCE_MINOR",
"SCALED_RADIUS_OF_GYRATION",
"... | [
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false,
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false,
false,
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false,
false,
false
] | 1,338 |
3,521 | predictive_accuracy | accuracy_score | oh15.wc | null | {0: [0 - cluster (numeric)],
1: [1 - infus (numeric)],
2: [2 - gland (numeric)],
3: [3 - dopamin (numeric)],
4: [4 - phagocytosi (numeric)],
5: [5 - fetal (numeric)],
6: [6 - signific (numeric)],
7: [7 - penetr (numeric)],
8: [8 - hepat (numeric)],
9: [9 - cigarett (numeric)],
10: [10 - fusion (numeric)],
11... | {'MajorityClassSize': 157.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 53.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 3101.0,
'NumberOfInstances': 913.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3100.0,
'NumberOfSymbolicFeatures': 1... | oh15.wc | [
"cluster",
"infus",
"gland",
"dopamin",
"phagocytosi",
"fetal",
"signific",
"penetr",
"hepat",
"cigarett",
"fusion",
"nitroprussid",
"rifampin",
"resist",
"huvec",
"rest",
"quadricep",
"goal",
"hydroxi",
"nucleotid",
"echocardiographi",
"agent",
"0",
"placem",
"juli",... | [
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f... | 1,339 |
363,594 | root_mean_squared_error | root_mean_squared_error | google_qa_question_type_reason_explanation | Given a question and an answer (from the Crowdsource team at Google) as well as additional
category features, predict the (subjective) type of the question in relation to the answer. These data
stem from the same source as qaa, where the different labels were both prediction targets in the
original (multi-l... | {0: [0 - question_title (string)],
1: [1 - question_body (string)],
2: [2 - question_user_name (string)],
3: [3 - question_user_page (string)],
4: [4 - answer (string)],
5: [5 - answer_user_name (string)],
6: [6 - answer_user_page (string)],
7: [7 - url (string)],
8: [8 - category (string)],
9: [9 - host (stri... | {'MajorityClassSize': nan,
'MaxNominalAttDistinctValues': nan,
'MinorityClassSize': nan,
'NumberOfClasses': 0.0,
'NumberOfFeatures': 40.0,
'NumberOfInstances': 4863.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 30.0,
'NumberOfSymbolicFeatures': 0.0,
'co... | google_qa_question_type_reason_explanation | [
"question_title",
"question_body",
"question_user_name",
"question_user_page",
"answer",
"answer_user_name",
"answer_user_page",
"url",
"category",
"host",
"question_asker_intent_understanding",
"question_body_critical",
"question_conversational",
"question_expect_short_answer",
"questio... | [
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false,
false,
false,
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false,
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false,
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false,
false,
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f... | 1,340 |
273 | predictive_accuracy | accuracy_score | spambase | **Author**: Mark Hopkins, Erik Reeber, George Forman, Jaap Suermondt
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/spambase)
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
SPAM E-mail Database
The "spam" concept is diverse: advertisements for products/websites, make mo... | {0: [0 - word_freq_make (numeric)],
1: [1 - word_freq_address (numeric)],
2: [2 - word_freq_all (numeric)],
3: [3 - word_freq_3d (numeric)],
4: [4 - word_freq_our (numeric)],
5: [5 - word_freq_over (numeric)],
6: [6 - word_freq_remove (numeric)],
7: [7 - word_freq_internet (numeric)],
8: [8 - word_freq_order (n... | {'MajorityClassSize': 2788.0,
'MaxNominalAttDistinctValues': 2.0,
'MinorityClassSize': 1813.0,
'NumberOfClasses': 2.0,
'NumberOfFeatures': 58.0,
'NumberOfInstances': 4601.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 57.0,
'NumberOfSymbolicFeatures': 1.0... | spambase | [
"word_freq_make",
"word_freq_address",
"word_freq_all",
"word_freq_3d",
"word_freq_our",
"word_freq_over",
"word_freq_remove",
"word_freq_internet",
"word_freq_order",
"word_freq_mail",
"word_freq_receive",
"word_freq_will",
"word_freq_people",
"word_freq_report",
"word_freq_addresses",
... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
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false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
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f... | 1,341 |
1,809 | predictive_accuracy | accuracy_score | splice | **Author**: Genbank. Donated by G. Towell, M. Noordewier, and J. Shavlik
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Splice-junction+Gene+Sequences))
**Please cite**: None
Primate splice-junction gene sequences (DNA) with associated imperfect domain theory.
Splice junctions are... | {0: [0 - Instance_name (nominal)],
1: [1 - attribute_1 (nominal)],
2: [2 - attribute_2 (nominal)],
3: [3 - attribute_3 (nominal)],
4: [4 - attribute_4 (nominal)],
5: [5 - attribute_5 (nominal)],
6: [6 - attribute_6 (nominal)],
7: [7 - attribute_7 (nominal)],
8: [8 - attribute_8 (nominal)],
9: [9 - attribute_9 ... | {'MajorityClassSize': 1655.0,
'MaxNominalAttDistinctValues': 6.0,
'MinorityClassSize': 767.0,
'NumberOfClasses': 3.0,
'NumberOfFeatures': 61.0,
'NumberOfInstances': 3190.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 61.0,... | splice | [
"attribute_1",
"attribute_2",
"attribute_3",
"attribute_4",
"attribute_5",
"attribute_6",
"attribute_7",
"attribute_8",
"attribute_9",
"attribute_10",
"attribute_11",
"attribute_12",
"attribute_13",
"attribute_14",
"attribute_15",
"attribute_16",
"attribute_17",
"attribute_18",
"... | [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true... | 1,342 |
1,805 | predictive_accuracy | accuracy_score | soybean | **Author**: R.S. Michalski and R.L. Chilausky (Donors: Ming Tan & Jeff Schlimmer)
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Soybean+(Large)) - 1988
**Please cite**: R.S. Michalski and R.L. Chilausky "Learning by Being Told and Learning from Examples: An Experimental Comparison of the Two Methods of ... | {0: [0 - date (nominal)],
1: [1 - plant-stand (nominal)],
2: [2 - precip (nominal)],
3: [3 - temp (nominal)],
4: [4 - hail (nominal)],
5: [5 - crop-hist (nominal)],
6: [6 - area-damaged (nominal)],
7: [7 - severity (nominal)],
8: [8 - seed-tmt (nominal)],
9: [9 - germination (nominal)],
10: [10 - plant-growth... | {'MajorityClassSize': 92.0,
'MaxNominalAttDistinctValues': 19.0,
'MinorityClassSize': 8.0,
'NumberOfClasses': 19.0,
'NumberOfFeatures': 36.0,
'NumberOfInstances': 683.0,
'NumberOfInstancesWithMissingValues': 121.0,
'NumberOfMissingValues': 2337.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 36.... | soybean | [
"date",
"plant-stand",
"precip",
"temp",
"hail",
"crop-hist",
"area-damaged",
"severity",
"seed-tmt",
"germination",
"plant-growth",
"leaves",
"leafspots-halo",
"leafspots-marg",
"leafspot-size",
"leaf-shread",
"leaf-malf",
"leaf-mild",
"stem",
"lodging",
"stem-cankers",
"c... | [
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true,
true,
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true,
true,
true,
true,
true,
true,
true,
true,
true
] | 1,343 |
1,890 | predictive_accuracy | accuracy_score | lymph | **Author**:
**Source**: Unknown -
**Please cite**:
Citation Request:
This lymphography domain was obtained from the University Medical Centre,
Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and
M. Soklic for providing the data. Please include this citation if you plan
... | {0: [0 - lymphatics (nominal)],
1: [1 - block_of_affere (nominal)],
2: [2 - bl_of_lymph_c (nominal)],
3: [3 - bl_of_lymph_s (nominal)],
4: [4 - by_pass (nominal)],
5: [5 - extravasates (nominal)],
6: [6 - regeneration_of (nominal)],
7: [7 - early_uptake_in (nominal)],
8: [8 - lym_nodes_dimin (numeric)],
9: [9 ... | {'MajorityClassSize': 81.0,
'MaxNominalAttDistinctValues': 8.0,
'MinorityClassSize': 2.0,
'NumberOfClasses': 4.0,
'NumberOfFeatures': 19.0,
'NumberOfInstances': 148.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3.0,
'NumberOfSymbolicFeatures': 16.0,
'co... | lymph | [
"lymphatics",
"block_of_affere",
"bl_of_lymph_c",
"bl_of_lymph_s",
"by_pass",
"extravasates",
"regeneration_of",
"early_uptake_in",
"lym_nodes_dimin",
"lym_nodes_enlar",
"changes_in_lym",
"defect_in_node",
"changes_in_node",
"changes_in_stru",
"special_forms",
"dislocation_of",
"excl... | [
true,
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false,
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true,
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] | 1,344 |
1,887 | predictive_accuracy | accuracy_score | audiology | **Author**: Professor Jergen at Baylor College of Medicine
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Audiology+(Standardized))
**Please cite**: Bareiss, E. Ray, & Porter, Bruce (1987). Protos: An Exemplar-Based Learning Apprentice. In the Proceedings of the 4th International Workshop on Machine Learning... | {0: [0 - age_gt_60 (nominal)],
1: [1 - air (nominal)],
2: [2 - airBoneGap (nominal)],
3: [3 - ar_c (nominal)],
4: [4 - ar_u (nominal)],
5: [5 - bone (nominal)],
6: [6 - boneAbnormal (nominal)],
7: [7 - bser (nominal)],
8: [8 - history_buzzing (nominal)],
9: [9 - history_dizziness (nominal)],
10: [10 - history... | {'MajorityClassSize': 57.0,
'MaxNominalAttDistinctValues': 24.0,
'MinorityClassSize': 1.0,
'NumberOfClasses': 24.0,
'NumberOfFeatures': 70.0,
'NumberOfInstances': 226.0,
'NumberOfInstancesWithMissingValues': 222.0,
'NumberOfMissingValues': 317.0,
'NumberOfNumericFeatures': 0.0,
'NumberOfSymbolicFeatures': 70.0... | audiology | [
"age_gt_60",
"air",
"airBoneGap",
"ar_c",
"ar_u",
"bone",
"boneAbnormal",
"bser",
"history_buzzing",
"history_dizziness",
"history_fluctuating",
"history_fullness",
"history_heredity",
"history_nausea",
"history_noise",
"history_recruitment",
"history_ringing",
"history_roaring",
... | [
true,
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true,
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true,
true,
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true,
true,
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true,
true,
true,
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true... | 1,345 |
242 | predictive_accuracy | accuracy_score | mfeat-factors | **Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology
**Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998
**Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html)
**Multiple Features Dataset: Factors**
One of a set of 6 d... | {0: [0 - att1 (numeric)],
1: [1 - att2 (numeric)],
2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
4: [4 - att5 (numeric)],
5: [5 - att6 (numeric)],
6: [6 - att7 (numeric)],
7: [7 - att8 (numeric)],
8: [8 - att9 (numeric)],
9: [9 - att10 (numeric)],
10: [10 - att11 (numeric)],
11: [11 - att12 (numeric)],
... | {'MajorityClassSize': 200.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 200.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 217.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 216.0,
'NumberOfSymbolicFeatures': 1... | mfeat-factors | [
"att1",
"att2",
"att3",
"att4",
"att5",
"att6",
"att7",
"att8",
"att9",
"att10",
"att11",
"att12",
"att13",
"att14",
"att15",
"att16",
"att17",
"att18",
"att19",
"att20",
"att21",
"att22",
"att23",
"att24",
"att25",
"att26",
"att27",
"att28",
"att29",
"att30... | [
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false,
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false,
false,
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f... | 1,346 |
3,527 | predictive_accuracy | accuracy_score | oh0.wc | null | {0: [0 - depart (numeric)],
1: [1 - cluster (numeric)],
2: [2 - nephropathi (numeric)],
3: [3 - sudden (numeric)],
4: [4 - infus (numeric)],
5: [5 - gland (numeric)],
6: [6 - dopamin (numeric)],
7: [7 - fetal (numeric)],
8: [8 - signific (numeric)],
9: [9 - penetr (numeric)],
10: [10 - hepat (numeric)],
11: ... | {'MajorityClassSize': 194.0,
'MaxNominalAttDistinctValues': 10.0,
'MinorityClassSize': 51.0,
'NumberOfClasses': 10.0,
'NumberOfFeatures': 3183.0,
'NumberOfInstances': 1003.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 3182.0,
'NumberOfSymbolicFeatures': ... | oh0.wc | [
"depart",
"cluster",
"nephropathi",
"sudden",
"infus",
"gland",
"dopamin",
"fetal",
"signific",
"penetr",
"hepat",
"cigarett",
"fairli",
"resist",
"agenc",
"rest",
"seropreval",
"goal",
"nucleotid",
"hydroxi",
"echocardiographi",
"decision",
"agent",
"0",
"tongue",
... | [
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false,
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false,
false,
false,
false,
f... | 1,347 |
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